debug

name

debug

description

Systematic debugging for kokoro-coreml: consult README/ (guides and learnings) and CLAUDE.md first, pull current library docs via Context7 MCP when coremltools/PyTorch/API behavior is uncertain, parallelize investigation with multiple subagents when stuck, prove fixes before calling success, then capture one consolidated note in README/Notes via **write-notes** as the **final** step before ending the session. For extreme cases, delegate a multi-agent audit via the Claude Code CLI. Use when the user invokes **debug**, **use debug**, asks to debug or fix a tricky bug, or work is blocked by unclear failure modes after quick local checks.

Debug

Purpose

Reduce guesswork: README/ and CLAUDE.md first, Context7 when library behavior is uncertain, parallel hypotheses when stuck, proof before “fixed”, one write-notes pass at session end, CLI multi-agent audit only for exceptional escalation.

Use When

• The user says debug, use the debug skill, debug this, or the task is bug investigation / root-cause analysis that is stalling.
• Failures involve coremltools, PyTorch, Core ML runtime, or Swift integration where training data may be stale—use Context7 before assuming APIs.

Do Not Use When

• The user only wants a trivial fix with an obvious stack trace and no doc ambiguity (still skim README/ if the area is known to be finicky).
• The task is greenfield feature build with no defect.

Workflow (in order)

1. Read repo knowledge first (mandatory)

Before writing code or deep-diving the stack:

1. Skim README/ for files that match the subsystem (conversion, export, Core ML runtime, tokenizer bridge, kokoro.js, etc.). Open the most relevant guides and look for known issues, workarounds, and checklists.
2. Skim README/Notes/ (when present) and high-level docs linked from README.md for past investigations.
3. Read README/Wiki/ and the relevant README/Guides/ for PyTorch → Core ML playbook constraints (static shapes, ANE layout, divide-and-conquer). CLAUDE.md is agent operating rules only.

2. Context7 MCP (library and platform docs)

When the bug touches coremltools, PyTorch, Swift Core ML, or related APIs:

1. Use Context7: resolve the library ID, then fetch focused docs for the API or behavior in question.
2. Prefer Context7 over memory or generic web search for API shape and version-sensitive behavior.

If Context7 is unavailable, fall back to official docs—do not invent APIs.

3. Reproduce and narrow

• Confirm minimal repro or the exact export step / predict call / log line that fails.
• State a one-sentence hypothesis and what evidence would falsify it.

4. Parallel investigation when stuck

If the problem is hard, cross-cutting, or you have been going in circles after the reproduce-and-narrow pass:

• In one turn, spin up multiple Task subagents with readonly: true and narrow charters (e.g. “MIL/export path only”, “Swift shapes only”).
• Merge overlapping hypotheses; avoid duplicate deep reads of the same file.

When in doubt, parallelize (same posture as audit, but hypothesis-driven).

5. Exceptionally frustrating bugs — CLI + audit

When still stuck after parallel investigation, or blast radius is high:

1. Use the Claude Code CLI from the repo root to run a multi-agent audit over the scoped slice that matters.
2. In the handoff, cite relevant README/ paths, symptom + ruled-out items, and instruct use of the audit skill with readonly subagents.

Escalation only—after README, Context7, and a fair parallel pass.

6. Prove the fix (before claiming success)

Do not say fixed until there is objective proof: failing test passes, export completes, Core ML predict matches tolerance, bad log line absent—whatever matches the bug.

7. Write notes once (mandatory last step)

After investigation, perform a single README/Notes/ update using write-notes (consolidate the session).

• One pass: symptom, repro, ruled out, root cause (TBD if unknown), fix, verification (proven / not), pointers to guides.
• Skip only when the user explicitly wants no note or the outcome is trivial.

Output expectations

• What was read from README/ / CLAUDE.md (paths).
• Verification: what proved the fix (or unverified / blocked).
• Which note file(s) were updated in step 7 (or why skipped).
• Whether Context7 was used and for which topic.
• Leading hypothesis(es) if still open, else root cause summary.

Anti-patterns

• Skipping README/ / CLAUDE.md to “save time.”
• Assuming API behavior without Context7 or official docs when versions matter.
• Serial thrashing instead of parallel charters.
• Declaring victory without verification.
• Patching notes throughout instead of one end-of-session pass.

Relation to other skills

• audit: structured review; use via CLI escalation when debug maxes out.
• write-notes: once at end of debug session.
• phase-audit: plan-phase checks—not the same as production debugging.