Chalk Labs
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Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/cogine-ai-investigate
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
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About
Use cases: testing
Reviews
Write a reviewNo reviews yet. Installed it? Reviews come from verified installers only. How reviews work
Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/investigate
Tools it pre-approves 6
From allowed-tools in SKILL.md: the agent may use these without asking you each time.
Bash,Read,Edit,Grep,Glob,Agent
What's inside
- Skill name
investigate- Description
- Systematic root-cause debugging. Use when: diagnosing bugs, investigating failures, debugging flaky tests, tracing unexpected behavior. Triggers on: '/investigate', 'debug this', 'why is this failing', 'find the root cause', 'flaky test'.
- License
- Apache-2.0
- Allowed tools
- Bash,, Read,, Edit,, Grep,, Glob,, Agent
- Instructions
- 144 lines in SKILL.md · view on GitHub
Before installing
- Pre-approves some shell commands
Files (1)
- SKILL.md
SKILL.md (first lines)
# Systematic Debugging Four-phase scientific method for root-cause analysis. Integrates with `slow-is-fast` reasoning principles. **Iron Law: No fix without verified root cause. Never say "this should fix it."** ## Phase 1: Root Cause Investigation ### 1.1 Collect Symptoms Gather all available evidence before forming any hypothesis: - Read the full error message/stack trace - Identify when it started (check `git log --oneline -20` for recent changes) - Determine reproduction conditions (always? intermittent? environment-specific?) - Check if there are related error reports or failing tests ### 1.2 Reproduce **A bug you can't reproduce is a bug you can't fix.** - Write down the exact reproduction steps - Confirm you can trigger the failure consistently - If intermittent: identify the variable (timing, data, concurrency, environment) ### 1.3 Narrow the Scope Use binary search thinking: - **Bisect in time**: `git log --oneline` — when did it last work? - **Bisect in space**: Which module/layer? Add strategic logging or assertions - **Bisect in data**: Which inputs trigger it? Minimal reproduction case Output after Phase 1: ``` Root cause hypothesis: <one sentence> Evidence: <what supports this> Confidence: <low/medium/high> ``` ## Phase 2: Pattern Analysis Match against known bug patterns before investigating from scratch: | Pattern | Signature | Where to Look | |---------|-----------|---------------| | **Race condition** | Intermittent, timing-dependent, "works on retry" | Shared state, async operations, missing locks/awaits | | **Nil/null propagation** | Crash on property access, "undefined is not a function" | Optional chaining gaps, missing null checks at boundaries | | **State corruption** | Wrong value at wrong time, stale data | Mutable shared state, cache invalidation, stale closures | | **Integration failure** | Works in isolation, fails in composition | API contract mismatch, version skew, env config | | **Config drift** | Works locally, fails in CI/staging/prod | Environment variables, feature flags, dependency versions | | **Stale cache** | Old behavior persists after fix, "but I already changed that" | Build cache, module cache, CDN, browser cache, ORM cache | | **Test pollution** | Test passes alone, fails in suite (or vice versa) | Shared global state, missing cleanup, execution order | ### For Flaky Tests Use the polluter-finding approach: 1. Run the failing test in isolation — does it pass? 2. If yes: another test is polluting shared state 3. Binary search the test suite to find the polluter: ```bash # Run first half of suite + failing test # If fails: polluter is in first half. Recurse. # If passes: polluter is in second half. Recurse. ``` 4. Once found: fix the shared state leak, don't just reorder tests ## Phase 3: Hypothesis Testing ### Scientific Method For each hypothesis: 1. **Predict**: "If hypothesis X is correct, then Y should be true" 2. **Test**: Design a minimal experiment that confirms or refutes 3. **Observe**: Record actual result — no interpretation yet 4. **Conclude**: Does evidence support or refute? Update hypothesis **Single variable**: Change only one thing per test. Multiple changes = uninterpretable results. ### 3-Strike Rule After **3 failed hypotheses**: - **STOP.** Do not try a 4th fix. - Reassess: you likely have the wrong mental model of the system - Ask: "What assumption am I making that could be wrong?" - Consider: is this an architectural issue, not a bug? - Present findings to user and ask for guidance ### Red Flags (you're on the wrong track) - Fix works but you don't understand why - Fix requires touching 5+ files for a "simple" bug - You're adding workarounds instead of fixing root cause - The "fix" breaks something else ## Phase 4: Implementation ### Fix Root Cause, Not Symptoms - **Wrong**: Adding a null check where null shouldn't be possible - **Right**: Fixing the code path that produces null ### Minimal Diff - Change only what's necessary for the fix - No drive-by refactoring during bug fixes - No "while I'm here" improvements ### Regression Test 1. Write a test that **fails** with the bug present 2. Apply the fix 3. Verify the test **passes** 4. Run the full test suite — no regressions ### Verification Report
From cogine-ai/cogine-dev-skillset, Apache-2.0.
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Signals
- Stars
- 3
- Forks
- 1
- Open issues
- 0
- Last commit (this folder)
- Apr 22, 2026 (6 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- Apache-2.0
- Repository
- github.com/cogine-ai/cogine-dev-skillset
- Website
- cogine.ai
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Done for you
Rather not set it up yourself?
Chalk Labs scopes, builds and runs agents for your team: the task audit, the eval harness, the integrations and the weekly ops report. Fixed scope, priced before we start.
See how we build AI agents →Read the case studies
Chalk Labs is a two-founder AI and growth studio. We build AI agents, CRMs and MVPs for Web3 and AI companies, and have shipped 50+ product and token launches.
- launches shipped
- 50+
- launches shipped
- media placements
- 500+
- media placements
- founders on every account
- 2
- founders on every account
Press we've placed: Forbes · CoinDesk · Decrypt · Cointelegraph · The Block
Rahil Jain, Co-founder, Chalk Labs. Ex-Goldman Sachs engineer. You talk to the person who builds it.
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Cite this page
investigate skill. Agent Mart. https://agentmart.dev/skills/cogine-ai-investigate (last updated 2026-10-24)