Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/thinking-machines-lab/tinker-cookbook/debugnpx skills add thinking-machines-lab/tinker-cookbook --skill debuggit clone --depth 1 https://github.com/thinking-machines-lab/tinker-cookbookWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/thinking-machines-lab/tinker-cookbook/debug)<a href="https://agentmods.dev/skills/thinking-machines-lab/tinker-cookbook/debug"><img src="https://agentmods.dev/badge/skills/thinking-machines-lab/tinker-cookbook/debug.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00154 | $0.08059 |
| Opus 5 | $0.00077 | $0.04029 |
| Sonnet 5 | $0.00031 | $0.01612 |
| Haiku 4.5 | $0.00015 | $0.00806 |
Grade A, and why
debug scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 656 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Tinker Debug
Systematic triage for training and deployment issues. Five triage paths:
- Performance issues — slow steps, hanging sessions, throughput problems
- Output correctness issues — mismatches between Tinker sampling and external inference engines
- Service availability — "is Tinker down?" quick diagnostics
- Renderer issues — wrong tokens, training quality degradation, prompt mismatches
- Error message decoder — mapping opaque errors to root causes
Identify which category the user's problem falls into, then follow the appropriate triage.
How the Tinker SDK works (essential context)
Understanding the SDK's threading model is key to diagnosing most issues. The SDK runs a background thread with its own asyncio event loop. All network I/O, heartbeats, and API result polling happen on this thread.
┌─────────────────────┐ ┌──────────────────────────────┐
│ Main Thread │ │ SDK Background Thread │
│ (user code) │ │ (asyncio event loop) │
│ │ │ │
│ fb = tc.fwd_bwd_ │────>│ HTTP POST /forward_backward │
│ async(data) │ │ → returns request_id │
│ │ │ │
│ # prepare next │ │ Long-poll /retrieve_future │
│ # batch here... │ │ (HTTP 408 = not ready yet) │
│ │ │ │
│ result = fb.result()│<────│ Result arrives → resolve │
│ # blocks until done │ │ │
│ │ │ Heartbeat every 10s │
└─────────────────────┘ └──────────────────────────────┘
When you call forward_backward_async(), the SDK:
- Submits the request coroutine to the background thread
- Returns a future immediately (main thread continues)
- Background thread sends HTTP request, starts long-polling for result
- Calling
.result()on the future blocks main thread until the background thread resolves it
What ships with it
5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago Changed · +1 lines b461ed08509c
- 4d ago First seen · 655 lines · 154 tokens per session scan A cbfd1be9912e
debug is a skill published in the GitHub repository thinking-machines-lab/tinker-cookbook (4,078 stars, last pushed 2d ago), licensed Apache-2.0. It adds 154 tokens to every session and 8,059 once invoked, about $0.0008 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…