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The productivity multiplier. /scrape discovers the flow; /skillify writes it as deterministic Playwright-via-browse-client code so the next /scrape on the same intent runs in ~200ms. 11-step flow with three locked contracts from the v1.19.0.0 plan review: D1 — Provenance guard. Walk back ≤10 agent turns for a clearly-bounded /scrape result. Refuse with one specific message if cold. No silent synthesis from chat fragments. D2 — Synthesis input slice. Extract ONLY the final-attempt $B calls that produced the JSON the user accepted, plus the user's intent string. Drop failed selectors, drop unrelated chat, drop earlier-session content. Closes Codex finding #6 by picking option (b) from the design doc: re-prompt from agent's own context, not a structured recorder. D3 — Atomic write. Stage to ~/.gstack/.tmp/skillify-<spawnId>/, run $B skill test against the temp dir, only rename into the final tier path on test pass + user approval. Test fail or approval reject = rm -rf the temp dir entirely. Default tier: global (~/.gstack/browser-skills/<name>/). --project flag overrides to per-project. Generated test must include at least one ★★ assertion (parsed JSON has expected shape + non-empty key fields), not a smoke ★ assertion. Bun runtime distribution (Codex finding #7) carries over to Phase 4. Documented in the skill's Limits section. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
435 lines
15 KiB
Cheetah
435 lines
15 KiB
Cheetah
---
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name: skillify
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version: 1.0.0
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description: |
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Codify the most recent successful /scrape flow into a permanent
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browser-skill on disk. Future /scrape calls with the same intent run
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the codified script in ~200ms instead of re-driving the page. Walks
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back through the conversation, synthesizes script.ts + script.test.ts
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+ fixture, runs the test in a temp dir, and asks before committing.
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Use when asked to "skillify", "codify", "save this scrape", or
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"make this permanent". (gstack)
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allowed-tools:
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- Bash
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- Read
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- Write
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- AskUserQuestion
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triggers:
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- skillify
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- codify this scrape
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- save this scrape
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- make this permanent
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---
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{{PREAMBLE}}
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# /skillify — codify the last scrape into a permanent skill
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The productivity multiplier. `/scrape` discovered how to pull the data;
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`/skillify` writes it as deterministic Playwright-via-`browse-client`
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code so the next `/scrape` call on the same intent runs in ~200ms.
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Without this command, `/scrape` is a slow wrapper around `$B`. With it,
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every successful scrape is a one-time cost.
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## Iron contract — never write a half-broken skill to disk
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Skills are user-trust artifacts. A broken skill in `$B skill list` makes
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agents reach for the wrong tool and erodes confidence. This skill writes
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to a temp dir, runs the auto-generated test there, and only renames into
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the final tier path on (a) test pass + (b) explicit user approval. On
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either failure, the temp dir is removed entirely. There is no "almost
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shipped" state.
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---
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## Step 1 — Provenance guard (D1)
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Walk back through the conversation, **at most 10 agent turns**, looking
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for the most recent `/scrape` invocation that:
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- Was bounded (you can identify the user's intent line and the trailing
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JSON the prototype produced)
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- Produced a JSON result the user did not subsequently invalidate
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(e.g., did not say "that's wrong", did not ask you to retry)
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If you cannot find one, refuse with exactly this message:
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> "No recent /scrape result found in this conversation. Run /scrape
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> <intent> first, then say /skillify."
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Stop. Do not synthesize from chat fragments. Do not synthesize from a
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match-path /scrape result (matched skills are already codified — there's
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nothing to skillify).
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If you find a candidate but the user is currently three turns past it
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discussing something unrelated, ask once before proceeding:
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> "The last successful /scrape was '<intent line>' a few turns back.
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> Skillify that one?"
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A "yes" lets you continue. Anything else: refuse with the message above.
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## Step 2 — Propose name + triggers
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From the prototype intent, extract:
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- A short skill name: lowercase letters/digits/dashes, ≤32 chars,
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starts with a letter, no consecutive dashes. E.g.,
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`lobsters-frontpage`, `gh-issue-list`, `pypi-package-stats`.
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- 3–5 trigger phrases the agent should match against in future `/scrape`
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calls. Mix the canonical phrase ("scrape lobsters frontpage") with
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paraphrases ("top posts on lobste.rs", "lobsters front page").
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- The host (just the hostname, e.g. `lobste.rs`).
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Then **AskUserQuestion** to confirm:
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```
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D<N> — Skill name + tier
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Project/branch/task: codifying /scrape "<intent>" as a browser-skill.
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ELI10: Pick a short name we'll use to find this skill next time you say
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something similar. Pick a tier — global means every project on this
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machine sees it, project means just this repo.
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Stakes if we pick wrong: bad name buries the skill in $B skill list;
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wrong tier means future projects can't find it (or can find it when you
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didn't want them to).
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Recommendation: A — <proposed-name> at global tier — most scrape skills
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generalize across projects.
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Note: options differ in kind, not coverage — no completeness score.
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A) Keep "<proposed-name>" at global tier — ~/.gstack/browser-skills/<proposed-name>/ (recommended)
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B) Keep "<proposed-name>" but at project tier — <project>/.gstack/browser-skills/<proposed-name>/
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C) Rename it (free-form — say the new name)
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```
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**Tier-shadowing check.** Before showing the question, run `$B skill list`
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and check for an existing skill at the same name. If found, add to the
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question:
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> "Note: a <tier> skill named '<name>' already exists. Picking the same
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> name at a higher tier (project > global > bundled) shadows it; picking
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> the same tier collides and will be refused at write time. Pick a
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> different name to coexist."
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## Step 3 — Synthesize `script.ts` (D2)
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**Use only the final-attempt `$B` calls** that produced the JSON the
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user accepted, plus the user's intent string. Drop:
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- Failed selector attempts (the four selectors you tried before the
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working one)
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- Unrelated `$B` commands from earlier turns
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- All conversation prose, summaries, your own reasoning
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The script imports the SDK from `./_lib/browse-client` (a sibling copy,
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written in step 6) and exports a parser function so `script.test.ts` can
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exercise it against the bundled fixture without spinning up the daemon.
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Mirror the bundled reference at `browser-skills/hackernews-frontpage/script.ts`:
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```ts
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import { browse } from './_lib/browse-client';
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export interface Item { /* one row of the JSON output */ }
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export interface Output { items: Item[]; count: number; }
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const TARGET_URL = '<the URL the prototype used>';
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export function parseFromHtml(html: string): Item[] {
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// Pure function: HTML in, parsed Item[] out. No $B calls.
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// Future fixture-replay tests call this directly.
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}
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if (import.meta.main) { await main(); }
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async function main(): Promise<void> {
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await browse.goto(TARGET_URL);
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const html = await browse.html();
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const items = parseFromHtml(html);
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const output: Output = { items, count: items.length };
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process.stdout.write(JSON.stringify(output) + '\n');
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}
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```
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The parser MUST be a pure function. If your prototype used multiple `$B`
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calls (e.g., goto + click "Next" + html), keep all of them in `main()`
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but extract the parsing into pure helpers. The fixture-replay tests in
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step 5 only exercise the pure parts.
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## Step 4 — Capture the fixture
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```bash
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$B goto "<TARGET_URL>"
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$B html > /tmp/skillify-fixture-$$.html
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```
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The fixture filename inside the staged dir is
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`fixtures/<host-with-dashes>-<YYYY-MM-DD>.html`, where the date is today.
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E.g. `fixtures/lobste-rs-2026-04-27.html`.
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Read the file you wrote, store its contents in a variable, and use it
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when staging in step 7.
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## Step 5 — Write `script.test.ts`
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Mirror `browser-skills/hackernews-frontpage/script.test.ts`. The test
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must include at least one ★★ assertion — parsed output has the expected
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shape AND non-empty key fields — not a smoke ★ assertion. Smoke tests
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that only check `parseFromHtml` doesn't throw are insufficient.
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```ts
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import { describe, it, expect } from 'bun:test';
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import * as fs from 'fs';
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import * as path from 'path';
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import { parseFromHtml } from './script';
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describe('<name> parser', () => {
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const fixturePath = path.join(import.meta.dir, 'fixtures', '<host>-<date>.html');
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const html = fs.readFileSync(fixturePath, 'utf-8');
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const items = parseFromHtml(html);
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it('returns at least one item from the bundled fixture', () => {
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expect(items.length).toBeGreaterThan(0);
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});
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it('every item has the required shape', () => {
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for (const item of items) {
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expect(typeof item.<keyfield>).toBe('<keytype>');
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// ... assert on every required field
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}
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});
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});
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```
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## Step 6 — Resolve the canonical SDK path + read it
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The canonical SDK lives at `<gstack-install>/browse/src/browse-client.ts`.
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The bundled-skill loader walks the install tree to find it; mirror that.
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Resolve the gstack install dir. Two reliable signals (in order):
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1. The bundled `hackernews-frontpage` skill — look at its tier path from
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`$B skill list` (the `bundled` row). The skill dir is
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`<gstack-install>/browser-skills/hackernews-frontpage/`, so the install
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dir is two `dirname` calls above its `_lib/browse-client.ts`.
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2. The active gstack skills install at `~/.claude/skills/gstack/`. Read
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the symlink target if it's a symlink, otherwise use the path directly.
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Example (run as Bun, not bash, to avoid shell-redirect parsing issues):
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```ts
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import * as fs from 'fs';
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import * as os from 'os';
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import * as path from 'path';
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function resolveSdkPath(): string {
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const candidates = [
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path.join(os.homedir(), '.claude', 'skills', 'gstack', 'browse', 'src', 'browse-client.ts'),
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// Add other install-dir candidates if your environment differs.
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];
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for (const c of candidates) {
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try {
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const real = fs.realpathSync(c);
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if (fs.existsSync(real)) return real;
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} catch {}
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}
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throw new Error('Could not resolve canonical browse-client.ts');
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}
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const sdkContents = fs.readFileSync(resolveSdkPath(), 'utf-8');
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```
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Read the SDK contents into a variable. The staging step writes it as
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`_lib/browse-client.ts` byte-identical to the canonical. Phase 1 decision
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#4 — each skill is fully self-contained, no version drift possible.
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## Step 7 — Stage the skill (D3 atomic write)
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Use the helper at `browse/src/browser-skill-write.ts`. Construct an inline
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TypeScript snippet (or shell out to a small Bun one-liner) that calls:
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```ts
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import { stageSkill } from '<gstack-install>/browse/src/browser-skill-write';
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const stagedDir = stageSkill({
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name: '<name>',
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files: new Map([
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['SKILL.md', skillMd],
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['script.ts', scriptTs],
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['script.test.ts', scriptTestTs],
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['_lib/browse-client.ts', sdkContents],
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['fixtures/<host>-<date>.html', fixtureHtml],
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]),
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});
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console.log(stagedDir);
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```
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The SKILL.md content for `<name>` follows the Phase 1 frontmatter
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contract:
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```yaml
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---
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name: <name>
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description: <one-line, what data this returns>
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host: <hostname>
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trusted: false # agent-authored skills are untrusted by default
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source: agent
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version: 1.0.0
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args: [] # extend if your script accepts --arg key=value
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triggers:
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- <phrase 1>
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- <phrase 2>
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- <phrase 3>
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---
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# <Name> scraper
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<2-3 sentences on what the script does, what URL it hits, and what
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shape of JSON it returns. NO conversation context. NO chat fragments.
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This is a durable on-disk artifact — keep it tight.>
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## Usage
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\`\`\`
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$ $B skill run <name>
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{ "items": [...], "count": N }
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\`\`\`
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```
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Capture `stagedDir` (the path returned by `stageSkill`). You'll pass it
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to `$B skill test` next, then to `commitSkill` or `discardStaged`.
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## Step 8 — Run `$B skill test` against the staged dir
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```bash
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$B skill test "<name>" --dir "<stagedDir>"
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```
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If `$B skill test` does not yet accept `--dir`, fall back to invoking the
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test runner directly against the staged path:
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```bash
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( cd "<stagedDir>" && bun test script.test.ts )
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```
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If the test fails:
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1. Read the test output. If the failure is a fixable parser bug,
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rewrite `script.ts` and `script.test.ts` (still inside the staged
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dir) and retry — at most twice. Show the diff to the user before
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each retry.
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2. If still failing after two retries, OR the failure is an
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environmental issue (SDK import, daemon connection):
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```ts
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import { discardStaged } from '<gstack-install>/browse/src/browser-skill-write';
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discardStaged('<stagedDir>');
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```
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Report the failure to the user, show them the staged `script.ts` for
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reference, and stop. No on-disk artifact.
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## Step 9 — Approval gate
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Tests passed. Now ask the user before committing:
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```
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D<N> — Commit skill "<name>" at <resolved-tier-path>?
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Project/branch/task: codified /scrape "<intent>" — tests pass against fixture.
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ELI10: The script ran clean against the snapshot we captured. Saying yes
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moves the staged folder into ~/.gstack/browser-skills/ where /scrape
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will find it next time. Saying no removes the staged folder and nothing
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lands on disk.
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Stakes if we pick wrong: yes commits an artifact you have to manually rm
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later if you regret it ($B skill rm <name> --global). No throws away
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~30s of synthesis work.
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Recommendation: A — tests passed, the script is self-contained, this is
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the productivity payoff for the prototype.
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Note: options differ in kind, not coverage — no completeness score.
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A) Commit it (recommended)
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B) Look at the script first (I'll print SKILL.md + script.ts and re-ask)
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C) Discard — don't commit
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```
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If the user picks B, print the staged `SKILL.md` and `script.ts` (NOT
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the fixture or _lib/), then re-ask the same A/B/C question (without B
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this time — they already saw it).
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## Step 10 — Commit (atomic) or discard
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If the user approved:
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```ts
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import { commitSkill } from '<gstack-install>/browse/src/browser-skill-write';
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const dest = commitSkill({
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name: '<name>',
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tier: '<global|project>', // from step 2 answer
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stagedDir: '<stagedDir>',
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});
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console.log(`Committed: ${dest}`);
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```
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If `commitSkill` throws "already exists" (tier-shadowing collision the
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user dismissed in step 2), report and ask whether to:
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- Pick a different name (back to step 2)
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- `$B skill rm <name>` then retry
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- Discard
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If the user rejected in step 9:
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```ts
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import { discardStaged } from '<gstack-install>/browse/src/browser-skill-write';
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discardStaged('<stagedDir>');
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```
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Report: "Discarded. No skill was written to disk."
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## Step 11 — Confirm + verify
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After a successful commit, run one verification:
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```bash
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$B skill list | grep <name>
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$B skill run <name> # should match the JSON the prototype produced
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```
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If the post-commit run does not match the prototype output, something
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in synthesis drifted. Surface this to the user — they may want to
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`$B skill rm <name>` and retry. Do NOT silently roll back; the user
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deserves to see the discrepancy.
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End the skill with one line: "Skill '<name>' committed at <tier>. Future
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/scrape calls matching '<canonical-trigger>' will run in ~200ms."
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---
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## Limits (be honest)
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- **Bun runtime required.** The codified skill runs as a Bun process
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(`bun run script.ts`). Phase 1 design carry-over (Codex finding #7).
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Real fix lands in Phase 4 (self-contained binary or Node fallback).
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For now: the skill works on any machine that has gstack installed,
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which means it has Bun.
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- **Fixture-replay tests are point-in-time.** When the target site
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rotates HTML, the fixture goes stale and the test passes against an
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outdated snapshot. Phase 4 will add fixture-staleness detection.
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- **Synthesis is best-effort.** You're writing a script from your own
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conversation memory. If the prototype was complex (multi-page, JS
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hydration, lazy load) the codified script may need a hand-edit before
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it's reliable. The post-commit verify step catches obvious drift.
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- **Single-target only.** One `$B goto` URL per skill. Multi-page
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crawls are out of scope — write a separate skill per target, or
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parameterize via `args:` if the URL pattern is regular.
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## What this skill does NOT do
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- Codify match-path /scrape results (matched skills are already codified)
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- Codify mutating flows (those are /automate's job — Phase 2 P0)
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- Run skills (that's `$B skill run` — codified skills are run via /scrape's
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match path or directly)
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- Edit existing skills ($EDITOR + the skill dir is the surface — `$B skill
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show <name>` finds the path)
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- Tombstone or remove ($B skill rm)
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{{LEARNINGS_LOG}}
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