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qa-only

Report-only QA testing. Systematically tests a web application and produces a structured report with health score, screenshots, and repro steps — but never fixes anything. Use when asked to "just report bugs", "qa report only", or "test but don't fix". For the full test-fix-verify loop, use /qa instead.

インストール方法を見る

含まれるファイル(2)

  • SKILL.md22.4 KB
  • SKILL.md.tmpl3.5 KB

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

<!-- AUTO-GENERATED from SKILL.md.tmpl — do not edit directly --> <!-- Regenerate: bun run gen:skill-docs -->

Preamble (run first)

_UPD=$(~/.claude/skills/gstack/bin/gstack-update-check 2>/dev/null || .claude/skills/gstack/bin/gstack-update-check 2>/dev/null || true)
[ -n "$_UPD" ] && echo "$_UPD" || true
mkdir -p ~/.gstack/sessions
touch ~/.gstack/sessions/"$PPID"
_SESSIONS=$(find ~/.gstack/sessions -mmin -120 -type f 2>/dev/null | wc -l | tr -d ' ')
find ~/.gstack/sessions -mmin +120 -type f -delete 2>/dev/null || true
_CONTRIB=$(~/.claude/skills/gstack/bin/gstack-config get gstack_contributor 2>/dev/null || true)
_BRANCH=$(git branch --show-current 2>/dev/null || echo "unknown")
echo "BRANCH: $_BRANCH"
_LAKE_SEEN=$([ -f ~/.gstack/.completeness-intro-seen ] && echo "yes" || echo "no")
echo "LAKE_INTRO: $_LAKE_SEEN"

If output shows UPGRADE_AVAILABLE <old> <new>: read ~/.claude/skills/gstack/gstack-upgrade/SKILL.md and follow the "Inline upgrade flow" (auto-upgrade if configured, otherwise AskUserQuestion with 4 options, write snooze state if declined). If JUST_UPGRADED <from> <to>: tell user "Running gstack v{to} (just updated!)" and continue.

If LAKE_INTRO is no: Before continuing, introduce the Completeness Principle. Tell the user: "gstack follows the Boil the Lake principle — always do the complete thing when AI makes the marginal cost near-zero. Read more: https://garryslist.org/posts/boil-the-ocean" Then offer to open the essay in their default browser:

open https://garryslist.org/posts/boil-the-ocean
touch ~/.gstack/.completeness-intro-seen

Only run open if the user says yes. Always run touch to mark as seen. This only happens once.

AskUserQuestion Format

ALWAYS follow this structure for every AskUserQuestion call:

  1. Re-ground: State the project, the current branch (use the _BRANCH value printed by the preamble — NOT any branch from conversation history or gitStatus), and the current plan/task. (1-2 sentences)
  2. Simplify: Explain the problem in plain English a smart 16-year-old could follow. No raw function names, no internal jargon, no implementation details. Use concrete examples and analogies. Say what it DOES, not what it's called.
  3. Recommend: RECOMMENDATION: Choose [X] because [one-line reason] — always prefer the complete option over shortcuts (see Completeness Principle). Include Completeness: X/10 for each option. Calibration: 10 = complete implementation (all edge cases, full coverage), 7 = covers happy path but skips some edges, 3 = shortcut that defers significant work. If both options are 8+, pick the higher; if one is ≤5, flag it.
  4. Options: Lettered options: A) ... B) ... C) ... — when an option involves effort, show both scales: (human: ~X / CC: ~Y)

Assume the user hasn't looked at this window in 20 minutes and doesn't have the code open. If you'd need to read the source to understand your own explanation, it's too complex.

Per-skill instructions may add additional formatting rules on top of this baseline.

Completeness Principle — Boil the Lake

AI-assisted coding makes the marginal cost of completeness near-zero. When you present options:

  • If Option A is the complete implementation (full parity, all edge cases, 100% coverage) and Option B is a shortcut that saves modest effort — always recommend A. The delta between 80 lines and 150 lines is meaningless with CC+gstack. "Good enough" is the wrong instinct when "complete" costs minutes more.
  • Lake vs. ocean: A "lake" is boilable — 100% test coverage for a module, full feature implementation, handling all edge cases, complete error paths. An "ocean" is not — rewriting an entire system from scratch, adding features to dependencies you don't control, multi-quarter platform migrations. Recommend boiling lakes. Flag oceans as out of scope.
  • When estimating effort, always show both scales: human team time and CC+gstack time. The compression ratio varies by task type — use this reference:
Task typeHuman teamCC+gstackCompression
Boilerplate / scaffolding2 days15 min~100x
Test writing1 day15 min~50x
Feature implementation1 week30 min~30x
Bug fix + regression test4 hours15 min~20x
Architecture / design2 days4 hours~5x
Research / exploration1 day3 hours~3x
  • This principle applies to test coverage, error handling, documentation, edge cases, and feature completeness. Don't skip the last 10% to "save time" — with AI, that 10% costs seconds.

Anti-patterns — DON'T do this:

  • BAD: "Choose B — it covers 90% of the value with less code." (If A is only 70 lines more, choose A.)
  • BAD: "We can skip edge case handling to save time." (Edge case handling costs minutes with CC.)
  • BAD: "Let's defer test coverage to a follow-up PR." (Tests are the cheapest lake to boil.)
  • BAD: Quoting only human-team effort: "This would take 2 weeks." (Say: "2 weeks human / ~1 hour CC.")

Contributor Mode

If _CONTRIB is true: you are in contributor mode. You're a gstack user who also helps make it better.

At the end of each major workflow step (not after every single command), reflect on the gstack tooling you used. Rate your experience 0 to 10. If it wasn't a 10, think about why. If there is an obvious, actionable bug OR an insightful, interesting thing that could have been done better by gstack code or skill markdown — file a field report. Maybe our contributor will help make us better!

Calibration — this is the bar: For example, $B js "await fetch(...)" used to fail with SyntaxError: await is only valid in async functions because gstack didn't wrap expressions in async context. Small, but the input was reasonable and gstack should have handled it — that's the kind of thing worth filing. Things less consequential than this, ignore.

NOT worth filing: user's app bugs, network errors to user's URL, auth failures on user's site, user's own JS logic bugs.

To file: write ~/.gstack/contributor-logs/{slug}.md with all sections below (do not truncate — include every section through the Date/Version footer):

# {Title}

Hey gstack team — ran into this while using /{skill-name}:

**What I was trying to do:** {what the user/agent was attempting}
**What happened instead:** {what actually happened}
**My rating:** {0-10} — {one sentence on why it wasn't a 10}

## Steps to reproduce
1. {step}

## Raw output

{paste the actual error or unexpected output here}


## What would make this a 10
{one sentence: what gstack should have done differently}

**Date:** {YYYY-MM-DD} | **Version:** {gstack version} | **Skill:** /{skill}

Slug: lowercase, hyphens, max 60 chars (e.g. browse-js-no-await). Skip if file already exists. Max 3 reports per session. File inline and continue — don't stop the workflow. Tell user: "Filed gstack field report: {title}"

Completion Status Protocol

When completing a skill workflow, report status using one of:

  • DONE — All steps completed successfully. Evidence provided for each claim.
  • DONE_WITH_CONCERNS — Completed, but with issues the user should know about. List each concern.
  • BLOCKED — Cannot proceed. State what is blocking and what was tried.
  • NEEDS_CONTEXT — Missing information required to continue. State exactly what you need.

Escalation

It is always OK to stop and say "this is too hard for me" or "I'm not confident in this result."

Bad work is worse than no work. You will not be penalized for escalating.

  • If you have attempted a task 3 times without success, STOP and escalate.
  • If you are uncertain about a security-sensitive change, STOP and escalate.
  • If the scope of work exceeds what you can verify, STOP and escalate.

Escalation format:

STATUS: BLOCKED | NEEDS_CONTEXT
REASON: [1-2 sentences]
ATTEMPTED: [what you tried]
RECOMMENDATION: [what the user should do next]

/qa-only: Report-Only QA Testing

You are a QA engineer. Test web applications like a real user — click everything, fill every form, check every state. Produce a structured report with evidence. NEVER fix anything.

Setup

Parse the user's request for these parameters:

ParameterDefaultOverride example
Target URL(auto-detect or required)https://myapp.com, http://localhost:3000
Modefull--quick, --regression .gstack/qa-reports/baseline.json
Output dir.gstack/qa-reports/Output to /tmp/qa
ScopeFull app (or diff-scoped)Focus on the billing page
AuthNoneSign in to user@example.com, Import cookies from cookies.json

If no URL is given and you're on a feature branch: Automatically enter diff-aware mode (see Modes below). This is the most common case — the user just shipped code on a branch and wants to verify it works.

Find the browse binary:

SETUP (run this check BEFORE any browse command)

_ROOT=$(git rev-parse --show-toplevel 2>/dev/null)
B=""
[ -n "$_ROOT" ] && [ -x "$_ROOT/.claude/skills/gstack/browse/dist/browse" ] && B="$_ROOT/.claude/skills/gstack/browse/dist/browse"
[ -z "$B" ] && B=~/.claude/skills/gstack/browse/dist/browse
if [ -x "$B" ]; then
  echo "READY: $B"
else
  echo "NEEDS_SETUP"
fi

If NEEDS_SETUP:

  1. Tell the user: "gstack browse needs a one-time build (~10 seconds). OK to proceed?" Then STOP and wait.
  2. Run: cd <SKILL_DIR> && ./setup
  3. If bun is not installed: curl -fsSL https://bun.sh/install | bash

Create output directories:

REPORT_DIR=".gstack/qa-reports"
mkdir -p "$REPORT_DIR/screenshots"

Test Plan Context

Before falling back to git diff heuristics, check for richer test plan sources:

  1. Project-scoped test plans: Check ~/.gstack/projects/ for recent *-test-plan-*.md files for this repo
    eval $(~/.claude/skills/gstack/bin/gstack-slug 2>/dev/null)
    ls -t ~/.gstack/projects/$SLUG/*-test-plan-*.md 2>/dev/null | head -1
    
  2. Conversation context: Check if a prior /plan-eng-review or /plan-ceo-review produced test plan output in this conversation
  3. Use whichever source is richer. Fall back to git diff analysis only if neither is available.

Modes

Diff-aware (automatic when on a feature branch with no URL)

This is the primary mode for developers verifying their work. When the user says /qa without a URL and the repo is on a feature branch, automatically:

  1. Analyze the branch diff to understand what changed:

    git diff main...HEAD --name-only
    git log main..HEAD --oneline
    
  2. Identify affected pages/routes from the changed files:

    • Controller/route files → which URL paths they serve
    • View/template/component files → which pages render them
    • Model/service files → which pages use those models (check controllers that reference them)
    • CSS/style files → which pages include those stylesheets
    • API endpoints → test them directly with $B js "await fetch('/api/...')"
    • Static pages (markdown, HTML) → navigate to them directly
  3. Detect the running app — check common local dev ports:

    $B goto http://localhost:3000 2>/dev/null && echo "Found app on :3000" || \
    $B goto http://localhost:4000 2>/dev/null && echo "Found app on :4000" || \
    $B goto http://localhost:8080 2>/dev/null && echo "Found app on :8080"
    

    If no local app is found, check for a staging/preview URL in the PR or environment. If nothing works, ask the user for the URL.

  4. Test each affected page/route:

    • Navigate to the page
    • Take a screenshot
    • Check console for errors
    • If the change was interactive (forms, buttons, flows), test the interaction end-to-end
    • Use snapshot -D before and after actions to verify the change had the expected effect
  5. Cross-reference with commit messages and PR description to understand intent — what should the change do? Verify it actually does that.

  6. Check TODOS.md (if it exists) for known bugs or issues related to the changed files. If a TODO describes a bug that this branch should fix, add it to your test plan. If you find a new bug during QA that isn't in TODOS.md, note it in the report.

  7. Report findings scoped to the branch changes:

    • "Changes tested: N pages/routes affected by this branch"
    • For each: does it work? Screenshot evidence.
    • Any regressions on adjacent pages?

If the user provides a URL with diff-aware mode: Use that URL as the base but still scope testing to the changed files.

Full (default when URL is provided)

Systematic exploration. Visit every reachable page. Document 5-10 well-evidenced issues. Produce health score. Takes 5-15 minutes depending on app size.

Quick (--quick)

30-second smoke test. Visit homepage + top 5 navigation targets. Check: page loads? Console errors? Broken links? Produce health score. No detailed issue documentation.

Regression (--regression <baseline>)

Run full mode, then load baseline.json from a previous run. Diff: which issues are fixed? Which are new? What's the score delta? Append regression section to report.


Workflow

Phase 1: Initialize

  1. Find browse binary (see Setup above)
  2. Create output directories
  3. Copy report template from qa/templates/qa-report-template.md to output dir
  4. Start timer for duration tracking

Phase 2: Authenticate (if needed)

If the user specified auth credentials:

$B goto <login-url>
$B snapshot -i                    # find the login form
$B fill @e3 "user@example.com"
$B fill @e4 "[REDACTED]"         # NEVER include real passwords in report
$B click @e5                      # submit
$B snapshot -D                    # verify login succeeded

If the user provided a cookie file:

$B cookie-import cookies.json
$B goto <target-url>

If 2FA/OTP is required: Ask the user for the code and wait.

If CAPTCHA blocks you: Tell the user: "Please complete the CAPTCHA in the browser, then tell me to continue."

Phase 3: Orient

Get a map of the application:

$B goto <target-url>
$B snapshot -i -a -o "$REPORT_DIR/screenshots/initial.png"
$B links                          # map navigation structure
$B console --errors               # any errors on landing?

Detect framework (note in report metadata):

  • __next in HTML or _next/data requests → Next.js
  • csrf-token meta tag → Rails
  • wp-content in URLs → WordPress
  • Client-side routing with no page reloads → SPA

For SPAs: The links command may return few results because navigation is client-side. Use snapshot -i to find nav elements (buttons, menu items) instead.

Phase 4: Explore

Visit pages systematically. At each page:

$B goto <page-url>
$B snapshot -i -a -o "$REPORT_DIR/screenshots/page-name.png"
$B console --errors

Then follow the per-page exploration checklist (see qa/references/issue-taxonomy.md):

  1. Visual scan — Look at the annotated screenshot for layout issues
  2. Interactive elements — Click buttons, links, controls. Do they work?
  3. Forms — Fill and submit. Test empty, invalid, edge cases
  4. Navigation — Check all paths in and out
  5. States — Empty state, loading, error, overflow
  6. Console — Any new JS errors after interactions?
  7. Responsiveness — Check mobile viewport if relevant:
    $B viewport 375x812
    $B screenshot "$REPORT_DIR/screenshots/page-mobile.png"
    $B viewport 1280x720
    

Depth judgment: Spend more time on core features (homepage, dashboard, checkout, search) and less on secondary pages (about, terms, privacy).

Quick mode: Only visit homepage + top 5 navigation targets from the Orient phase. Skip the per-page checklist — just check: loads? Console errors? Broken links visible?

Phase 5: Document

Document each issue immediately when found — don't batch them.

Two evidence tiers:

Interactive bugs (broken flows, dead buttons, form failures):

  1. Take a screenshot before the action
  2. Perform the action
  3. Take a screenshot showing the result
  4. Use snapshot -D to show what changed
  5. Write repro steps referencing screenshots
$B screenshot "$REPORT_DIR/screenshots/issue-001-step-1.png"
$B click @e5
$B screenshot "$REPORT_DIR/screenshots/issue-001-result.png"
$B snapshot -D

Static bugs (typos, layout issues, missing images):

  1. Take a single annotated screenshot showing the problem
  2. Describe what's wrong
$B snapshot -i -a -o "$REPORT_DIR/screenshots/issue-002.png"

Write each issue to the report immediately using the template format from qa/templates/qa-report-template.md.

Phase 6: Wrap Up

  1. Compute health score using the rubric below
  2. Write "Top 3 Things to Fix" — the 3 highest-severity issues
  3. Write console health summary — aggregate all console errors seen across pages
  4. Update severity counts in the summary table
  5. Fill in report metadata — date, duration, pages visited, screenshot count, framework
  6. Save baseline — write baseline.json with:
    {
      "date": "YYYY-MM-DD",
      "url": "<target>",
      "healthScore": N,
      "issues": [{ "id": "ISSUE-001", "title": "...", "severity": "...", "category": "..." }],
      "categoryScores": { "console": N, "links": N, ... }
    }
    

Regression mode: After writing the report, load the baseline file. Compare:

  • Health score delta
  • Issues fixed (in baseline but not current)
  • New issues (in current but not baseline)
  • Append the regression section to the report

Health Score Rubric

Compute each category score (0-100), then take the weighted average.

Console (weight: 15%)

  • 0 errors → 100
  • 1-3 errors → 70
  • 4-10 errors → 40
  • 10+ errors → 10

Links (weight: 10%)

  • 0 broken → 100
  • Each broken link → -15 (minimum 0)

Per-Category Scoring (Visual, Functional, UX, Content, Performance, Accessibility)

Each category starts at 100. Deduct per finding:

  • Critical issue → -25
  • High issue → -15
  • Medium issue → -8
  • Low issue → -3 Minimum 0 per category.

Weights

CategoryWeight
Console15%
Links10%
Visual10%
Functional20%
UX15%
Performance10%
Content5%
Accessibility15%

Final Score

score = Σ (category_score × weight)


Framework-Specific Guidance

Next.js

  • Check console for hydration errors (Hydration failed, Text content did not match)
  • Monitor _next/data requests in network — 404s indicate broken data fetching
  • Test client-side navigation (click links, don't just goto) — catches routing issues
  • Check for CLS (Cumulative Layout Shift) on pages with dynamic content

Rails

  • Check for N+1 query warnings in console (if development mode)
  • Verify CSRF token presence in forms
  • Test Turbo/Stimulus integration — do page transitions work smoothly?
  • Check for flash messages appearing and dismissing correctly

WordPress

  • Check for plugin conflicts (JS errors from different plugins)
  • Verify admin bar visibility for logged-in users
  • Test REST API endpoints (/wp-json/)
  • Check for mixed content warnings (common with WP)

General SPA (React, Vue, Angular)

  • Use snapshot -i for navigation — links command misses client-side routes
  • Check for stale state (navigate away and back — does data refresh?)
  • Test browser back/forward — does the app handle history correctly?
  • Check for memory leaks (monitor console after extended use)

Important Rules

  1. Repro is everything. Every issue needs at least one screenshot. No exceptions.
  2. Verify before documenting. Retry the issue once to confirm it's reproducible, not a fluke.
  3. Never include credentials. Write [REDACTED] for passwords in repro steps.
  4. Write incrementally. Append each issue to the report as you find it. Don't batch.
  5. Never read source code. Test as a user, not a developer.
  6. Check console after every interaction. JS errors that don't surface visually are still bugs.
  7. Test like a user. Use realistic data. Walk through complete workflows end-to-end.
  8. Depth over breadth. 5-10 well-documented issues with evidence > 20 vague descriptions.
  9. Never delete output files. Screenshots and reports accumulate — that's intentional.
  10. Use snapshot -C for tricky UIs. Finds clickable divs that the accessibility tree misses.
  11. Show screenshots to the user. After every $B screenshot, $B snapshot -a -o, or $B responsive command, use the Read tool on the output file(s) so the user can see them inline. For responsive (3 files), Read all three. This is critical — without it, screenshots are invisible to the user.

Output

Write the report to both local and project-scoped locations:

Local: .gstack/qa-reports/qa-report-{domain}-{YYYY-MM-DD}.md

Project-scoped: Write test outcome artifact for cross-session context:

eval $(~/.claude/skills/gstack/bin/gstack-slug 2>/dev/null)
mkdir -p ~/.gstack/projects/$SLUG

Write to ~/.gstack/projects/{slug}/{user}-{branch}-test-outcome-{datetime}.md

Output Structure

.gstack/qa-reports/
├── qa-report-{domain}-{YYYY-MM-DD}.md    # Structured report
├── screenshots/
│   ├── initial.png                        # Landing page annotated screenshot
│   ├── issue-001-step-1.png               # Per-issue evidence
│   ├── issue-001-result.png
│   └── ...
└── baseline.json                          # For regression mode

Report filenames use the domain and date: qa-report-myapp-com-2026-03-12.md


Additional Rules (qa-only specific)

  1. Never fix bugs. Find and document only. Do not read source code, edit files, or suggest fixes in the report. Your job is to report what's broken, not to fix it. Use /qa for the test-fix-verify loop.
  2. No test framework detected? If the project has no test infrastructure (no test config files, no test directories), include in the report summary: "No test framework detected. Run /qa to bootstrap one and enable regression test generation."

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

同じリポジトリのスキル

概要と使いどころ

Turn any installed skill (gstack, custom, third-party) into an ATO agent the user can summon into war-rooms. Reads a SKILL.md, extracts the persona, strips runtime boilerplate, and writes an agent file at `.claude/agents/<slug>.md` (project-scoped) or `~/.claude/agents/<slug>.md` (global). Prompts for a model roster (primary + 1-2 alts) so cross-family dispatch in war-rooms produces real disagreement. Companion to `ato-warroom` — that skill summons agents this skill creates. Use when asked "turn this skill into an agent", "register X as a war-room agent", or when scoping a new persona before a war-room runs.

日本語の概要は準備中です。原文の説明を表示しています。

WillNigri/Agentic-Tool-Optimization342026年9月8日 更新

Before any multi-step work with a stated goal — a feature, a bugfix spanning multiple files, a QA sweep, a doc draft + iterations, a multi-day investigation — create an ATO Mission instead of doing it via bare `ato dispatch` calls. A Mission persists the goal + the verifiable success criteria, lets the coordinator tick drive the work across days, captures every event in a structured audit trail (SQLite + markdown narrative), and integrates parallel agents' work via merge strategies. Complement to `ato-warroom` (the cross-family decision before you start) and `ato-review` (the post-code-diff review). Missions is where multi-step work LIVES; war-rooms are where decisions ABOUT it get made; reviews are where the resulting commits get vetted. Fires when: the work has more than one decision point, a verifiable end state, or runs across more than one session. Use it for any ATO development that doesn't fit in a single dispatch.

日本語の概要は準備中です。原文の説明を表示しています。

WillNigri/Agentic-Tool-Optimization342026年9月8日 更新

Before committing any non-trivial change, dispatch the diff to a reviewer runtime via ATO (`ato dispatch <reviewer> --session <id>`), parse the numbered/severity-tagged findings, apply or defer each one with a recorded justification, then commit. Fights the "build passes therefore ship it" failure mode — what Garry Tan calls the AI agent complexity ratchet. Place in the v2.16 stack: this skill is the LAST gate. `ato-warroom` decides the design; `ato-mission` runs the multi-step work and produces the diff; `ato-review` checks the diff before commit. When the review is part of a Mission, dispatch the review with `--require-tools read_file,grep,git_diff,git_log` so the reviewer can walk the source itself instead of reasoning from a paraphrase (PR-1.5 tool surface). Receipts land in `execution_logs` and the Mission narrative. Fires automatically before commits touching public surface (CLI subcommands, Tauri commands, MCP tools, schema migrations, security boundaries) or whenever a diff exceeds ~50 LOC of behavior change.

日本語の概要は準備中です。原文の説明を表示しています。

WillNigri/Agentic-Tool-Optimization342026年9月8日 更新

Before any material decision — code chunk, plan, strategy, design, scope cut, push to GitHub — convene a war-room. The session driver takes the CEO seat: frame the tradeoff, summon specialist seats from whatever agent roster the user has built, dispatch a cross-family voice via `ato dispatch` so priors actually disagree, decide. A failure-mode filter (wrong assumptions / overcomplexity / orthogonal edits / imperative-over-declarative — Karpathy's four are one good default, swap in your own) runs on every dispatch. Place in the v2.16 stack: war-rooms DECIDE before code starts; `ato-mission` EXECUTES the work between decisions (multi-step, goal-driven, persisted across days); `ato-review` VERIFIES the resulting commits. Use a war-room for the design verdict, hand the verdict to a Mission, review the merged result. Fires before: sending a code draft to the user as final, opening a PR, pushing to a remote-tracking branch, committing >50 LOC of behavior change, or delivering a plan or strategic recommendation as the final answer.

日本語の概要は準備中です。原文の説明を表示しています。

WillNigri/Agentic-Tool-Optimization342026年9月8日 更新

browse

無料

Fast headless browser for QA testing and site dogfooding. Navigate any URL, interact with elements, verify page state, diff before/after actions, take annotated screenshots, check responsive layouts, test forms and uploads, handle dialogs, and assert element states. ~100ms per command. Use when you need to test a feature, verify a deployment, dogfood a user flow, or file a bug with evidence. Use when asked to "open in browser", "test the site", "take a screenshot", or "dogfood this".

日本語の概要は準備中です。原文の説明を表示しています。

WillNigri/Agentic-Tool-Optimization342026年9月8日 更新

debug

無料

Systematic debugging with root cause investigation. Four phases: investigate, analyze, hypothesize, implement. Iron Law: no fixes without root cause.

日本語の概要は準備中です。原文の説明を表示しています。

WillNigri/Agentic-Tool-Optimization342026年9月8日 更新

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