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 skills add dnlbox/ai-protocol --skill shape-conceptgit clone --depth 1 https://github.com/dnlbox/ai-protocolWrote 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/dnlbox/ai-protocol/shape-concept)<a href="https://agentmods.dev/skills/dnlbox/ai-protocol/shape-concept"><img src="https://agentmods.dev/badge/skills/dnlbox/ai-protocol/shape-concept/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/skills/dnlbox/ai-protocol/shape-concept"><img src="https://agentmods.dev/badge/skills/dnlbox/ai-protocol/shape-concept.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 | $0.00017 | $0.00547 |
| Opus 5.5 | $0.00007 | $0.00219 |
| Sonnet 5.5 | $0.00003 | $0.00109 |
| Haiku 4.5 | $0.00002 | $0.00055 |
Grade A, and why
shape-concept 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 1mo 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 — 76 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Shape concept
Use this skill after concept intake or when accepted product intent must change deliberately.
Start
- Read
docs/intake/concept-intake.md. - Read every existing file in
docs/concept/. - Require intake status
Ready for concept shapingfor initial shaping. - Require an explicit product-change request for re-shaping.
- Treat placeholder files as scaffolding.
- Treat accepted concept files as product authority.
- Treat intake as historical input during re-shaping.
- Return to concept intake when the intake is materially incomplete.
Document shape
- Choose the smallest useful concept document set.
- Give each concept file one ownership boundary.
- Keep
docs/concept/README.mdas the concept index. - Use status
Shapingduring initial drafting. - Use status
Re-shapingduring deliberate revision. - Avoid a fixed document taxonomy.
- Avoid one file per minor topic.
- Avoid duplicating a decision across files.
Drafting
- Synthesise the intake by meaning.
- Separate settled intent from assumptions.
- Separate evidence-backed findings from product judgements.
- Separate explicit exclusions from open questions.
- Cite factual claims with links or local sources.
- Mark unsupported product judgements as hypotheses.
- Preserve compatible human additions.
- Preserve unresolved non-blocking questions.
- Keep each discussion round focused on one tension.
- Ask for one material product decision at a time.
- Conduct research only when the user requests it.
- Fold approved research into the relevant concept file.
- Avoid detached research dumps.
Boundaries
- Write only within
docs/concept/. - Update intake status only when the stage changes.
- Avoid choosing frameworks during concept shaping.
- Avoid choosing schemas during concept shaping.
- Avoid choosing deployment topology during concept shaping.
- Avoid turning open product questions into implementation discretion.
- Stop before implementation planning.
- Stop before product implementation.
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.
- 1mo ago First seen · 76 lines · 17 tokens per session scan A 91e808361f42
shape-concept is a skill published in the GitHub repository dnlbox/ai-protocol (19 stars, last pushed 2mo ago), licensed MIT. It adds 17 tokens to every session and 547 once invoked, about $0.0001 per session on Opus 5.5. 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.
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