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v1.33.1.0 fix(learnings): token-OR query + task-shaped retrieval in 3 long skills (#1442)

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* fix(learnings): use token-OR matching in gstack-learnings-search --query

Split the query on whitespace into tokens; a learning matches if ANY
token appears as a substring in ANY of key/insight/files. Previously
the whole query was a single substring, so multi-word queries like
"debug investigation" only matched learnings whose insight contained
that exact contiguous phrase, which is usually nothing.

Whitespace-only query falls through to no-query (matches today's no-flag
behavior). Single-word queries behave exactly as before.

Adds test/gstack-learnings-search.test.ts: 3 assertions covering
multi-token, single-token, and no-query backwards compat.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

* feat(resolver): parameterized LEARNINGS_SEARCH with shell-injection guard

The {{LEARNINGS_SEARCH}} macro now accepts a query=KEYWORD argument that
gets interpolated as --query "<keyword>" into the generated bash. Empty
value falls through to no-query (principle of least surprise: a stray
{{LEARNINGS_SEARCH:query=}} placeholder gets today's behavior, not a
build failure). Pattern reuses the parameterized-macro parsing from
composition.ts. The 13 templates that don't pass a query stay
byte-identical in their generated SKILL.md output.

Shell-injection guard: the query value is whitelisted to
^[A-Za-z0-9 _-]+$ at gen-skill-docs time. Any \$(), backticks,
semicolons, or quotes throw a loud build error instead of emitting
executable bash. Static template queries are safe by inspection;
this defends against future contributors writing dangerous values.

Adds 5 assertions to test/gen-skill-docs.test.ts covering no-args,
claude+query=foo bar on both cross-project and project-scoped branches,
codex host variant, empty value semantics, and shell-injection payloads
(\$(whoami), backticks, ;, &, ", \\, \$x) throwing build errors.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

* feat(skills): task-shaped queries + mid-flow refresh in /investigate /qa /ship

The three long skills now pull learnings keyed to their theme at the
top, then re-pull at phase boundaries as work shifts to new sub-tasks.

Top-of-skill queries (5-6 token unions, token-OR matched):
- investigate: "debug investigation root cause hypothesis bug fix"
- qa: "qa testing bug regression flake fixture"
- ship: "release ship version changelog merge pr"

Mid-flow refresh blocks (concrete keyword recipe + worked examples):
- investigate: between Phase 1 (hypothesis) and Phase 2 (analysis),
  keyed to the hypothesis noun. Examples: auth-cookie, session-expiry.
- qa: between Phase 7 (triage) and Phase 8 (fix loop), keyed to the
  buggy component name. Examples: checkout-button, signup-form.
- ship: just before Step 12 (VERSION bump), keyed to the headline
  feature. Examples: learnings-search, pacing, worktree-ship.

Keyword recipe enforces alphanumeric+hyphen only (no quotes, slashes,
dots, colons) so dynamic queries cannot inject shell metacharacters.

The other 13 short-lived skills keep the bare {{LEARNINGS_SEARCH}} form.
Backwards-compat verified via diff: their generated SKILL.md output is
byte-identical to before this change.

Golden ship fixtures regenerated to match the new ship/SKILL.md output.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

* chore: bump version and changelog (v1.33.1.0)

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

* test: refresh codex+factory ship golden fixtures

Follow-up to 513c9660 — the codex and factory host outputs needed
regeneration too, missed in the initial commit because gen:skill-docs
was only run for the claude host. Now matches gen:skill-docs --host all.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

---------

Co-authored-by: Claude Opus 4.7 <noreply@anthropic.com>
This commit is contained in:
Garry Tan
2026-05-11 19:34:33 -07:00
committed by GitHub
co-authored by Claude Opus 4.7
parent d21ba06b5a
commit 1a4f0c9c15
16 changed files with 365 additions and 27 deletions
Download Patch File Download Diff File Expand all files Collapse all files
investigate/SKILL.md
+16 -2
View File
@@ -823,9 +823,9 @@ Search for relevant learnings from previous sessions:
_CROSS_PROJ=$(~/.claude/skills/gstack/bin/gstack-config get cross_project_learnings 2>/dev/null || echo "unset")
echo "CROSS_PROJECT: $_CROSS_PROJ"
if [ "$_CROSS_PROJ" = "true" ]; then
~/.claude/skills/gstack/bin/gstack-learnings-search --limit 10 --cross-project 2>/dev/null || true
~/.claude/skills/gstack/bin/gstack-learnings-search --limit 10 --query "debug investigation root cause hypothesis bug fix" --cross-project 2>/dev/null || true
else
~/.claude/skills/gstack/bin/gstack-learnings-search --limit 10 2>/dev/null || true
~/.claude/skills/gstack/bin/gstack-learnings-search --limit 10 --query "debug investigation root cause hypothesis bug fix" 2>/dev/null || true
fi
```
@@ -855,6 +855,20 @@ smarter on their codebase over time.
Output: **"Root cause hypothesis: ..."** — a specific, testable claim about what is wrong and why.
### Refresh learnings for the hypothesis you just named
The top-of-skill learnings pull above is keyed to "debug investigation" broadly. Now that you have a specific hypothesis, re-pull learnings keyed to that hypothesis so prior fixes for the same problem-shape surface.
Pick ONE keyword from the hypothesis. The keyword should be a noun: the failing component name, the basename of the file you suspect (without extension), or the bug noun. The keyword MUST be alphanumeric or hyphen only — no quotes, slashes, dots, colons, or whitespace. If your candidate has any of those, simplify to just the alphanumeric stem.
Worked examples (investigate-specific): good keywords are `auth-cookie`, `session-expiry`, `redirect-loop`. Bad: `auth.ts:47`, `fix the auth bug`, `<hypothesis-keyword>`.
```bash
~/.claude/skills/gstack/bin/gstack-learnings-search --query "<your-keyword>" --limit 5 2>/dev/null || true
```
If any learnings come back, name which one applies to your investigation in one sentence. If none come back, continue without reference — the absence of a matching prior learning is itself useful information.
---
## Scope Lock
investigate/SKILL.md.tmpl
+15 -1
View File
@@ -93,10 +93,24 @@ Gather context before forming any hypothesis.
5. **Check investigation history:** Search prior learnings for investigations on the same files. Recurring bugs in the same area are an architectural smell. If prior investigations exist, note patterns and check if the root cause was structural.
{{LEARNINGS_SEARCH}}
{{LEARNINGS_SEARCH:query=debug investigation root cause hypothesis bug fix}}
Output: **"Root cause hypothesis: ..."** — a specific, testable claim about what is wrong and why.
### Refresh learnings for the hypothesis you just named
The top-of-skill learnings pull above is keyed to "debug investigation" broadly. Now that you have a specific hypothesis, re-pull learnings keyed to that hypothesis so prior fixes for the same problem-shape surface.
Pick ONE keyword from the hypothesis. The keyword should be a noun: the failing component name, the basename of the file you suspect (without extension), or the bug noun. The keyword MUST be alphanumeric or hyphen only — no quotes, slashes, dots, colons, or whitespace. If your candidate has any of those, simplify to just the alphanumeric stem.
Worked examples (investigate-specific): good keywords are `auth-cookie`, `session-expiry`, `redirect-loop`. Bad: `auth.ts:47`, `fix the auth bug`, `<hypothesis-keyword>`.
```bash
~/.claude/skills/gstack/bin/gstack-learnings-search --query "<your-keyword>" --limit 5 2>/dev/null || true
```
If any learnings come back, name which one applies to your investigation in one sentence. If none come back, continue without reference — the absence of a matching prior learning is itself useful information.
---
## Scope Lock