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.
git clone --depth 1 https://github.com/product-on-purpose/thinking-framework-skillsWrote 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/commands/product-on-purpose/thinking-framework-skills/think-pdca-a3)<a href="https://agentmods.dev/commands/product-on-purpose/thinking-framework-skills/think-pdca-a3"><img src="https://agentmods.dev/badge/commands/product-on-purpose/thinking-framework-skills/think-pdca-a3/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/product-on-purpose/thinking-framework-skills/think-pdca-a3"><img src="https://agentmods.dev/badge/commands/product-on-purpose/thinking-framework-skills/think-pdca-a3.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00049 | $0.00532 |
| Opus 5 | $0.00024 | $0.00266 |
| Sonnet 5 | $0.00010 | $0.00106 |
| Haiku 4.5 | $0.00005 | $0.00053 |
Grade A, and why
think-pdca-a3 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 10d 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.
What it actually says
Run the think-pdca-a3 recipe: 3 skills chained in a fixed order, carrying forward only the compressed artifact at each handoff.
The compression is the point. Do not paste a whole artifact into the next step; carry exactly what each handoff names, so the chain stays cheaper and sharper than running the skills back to back.
PDCA (Plan-Do-Check-Act, the Shewhart/Deming improvement cycle; Deming preferred Plan-Do-Study-Act) and Toyota's A3 are not a separate skill here: the reflective heart of the loop already ships as after-action-review, the forward half is execution plus a "repeat" instruction, and the A3 one-page layout is a document convention. This recipe chains the shipped moves rather than duplicating after-action-review under a more famous industrial name.
Run the steps in order, carrying forward only the compressed artifact between them:
think-issue-tree(Plan, root cause) -> carry the root cause of the performance gap. Swap inthink-iceberg-modelwhen the gap is systemic (events down to structures and mental models) rather than a decomposable deviation.think-decision-option-review(Plan, countermeasure) -> carry the chosen countermeasure to test.- (Do - run the change in the world; this emits no thinking artifact and the library does not own it.)
think-after-action-review(Check) -> carry expected versus actual, the why, and what to sustain or change.- (Act - standardize if it worked, adjust and re-run if not; a control-flow wrapper, then loop back to step 1.)
Composite artifact: an improvement-cycle record - the root cause, the countermeasure tested, the actual-versus-expected review, and the standardize-or-iterate decision. Full prose and rationale: recipes/pdca-a3.md.
Apply the chain to: $ARGUMENTS
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.
- 10d ago First seen · 25 lines · 49 tokens per session scan A e9a4d6782167
think-pdca-a3 is a command published in the GitHub repository product-on-purpose/thinking-framework-skills (15 stars, last pushed 24d ago), licensed Apache-2.0. It adds 49 tokens to every session and 532 once invoked, about $0.0002 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 commands, from other repositories
doff
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speckit.polish
Polish and complete speckit workflow — quality gate, docs, changelog, MR.
review
Recent git commits: !git log --oneline -10.
session-recap
Summarize recent CHANGELOG.md entries for context restoration. Parses the canonical heading shape ## YYYY-MM-DD — pass-N — summary. Filters: last N (default 10), YYYY-MM date prefix, or "today". Supports --json for machine-readable output.
incident-response
Start structured incident response with automatic triage, communication, and resolution tracking.
resolve-conflict
Systematic merge conflict resolution with context analysis.