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 shinpr/ai-coding-project-boilerplate --skill requirement-convergencegit clone --depth 1 https://github.com/shinpr/ai-coding-project-boilerplateWrote 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/shinpr/ai-coding-project-boilerplate/requirement-convergence)<a href="https://agentmods.dev/skills/shinpr/ai-coding-project-boilerplate/requirement-convergence"><img src="https://agentmods.dev/badge/skills/shinpr/ai-coding-project-boilerplate/requirement-convergence/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/shinpr/ai-coding-project-boilerplate/requirement-convergence"><img src="https://agentmods.dev/badge/skills/shinpr/ai-coding-project-boilerplate/requirement-convergence.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00067 | $0.00937 |
| Opus 5 | $0.00034 | $0.00468 |
| Sonnet 5 | $0.00013 | $0.00187 |
| Haiku 4.5 | $0.00007 | $0.00094 |
Grade A, and why
requirement-convergence 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 4d 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 — 70 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Requirement Convergence
Purpose
Requirements arrive bloated, ambiguous, or aimed at the wrong outcome. A capable model reconciles all three into a coherent plan and builds it faithfully — delivering exactly what was asked for when what was asked for was wrong.
This skill converges what to build. How to build it, and which documents the change requires, are settled after the what is.
Convergence Fields
| Field | Pass condition |
|---|---|
outcome |
One observable result. A requirement that does not serve it is excess. |
requirements[] |
Every build-relevant item labeled current-state or desired-future. |
nonGoals[] |
Authored by the user, or the user stated there are none. |
cost |
A band with the structural evidence that places it, plus the unknowns that remain. |
cost is a rough band, not the effort estimate a work plan schedules against; requirements cannot support person-days. Its unknowns carry more decision weight than its size.
Keep request signals classified as evaluation requests, speculative ideas, or prescribed mechanisms in active convergence context as judgment-only candidates. requirements[] and durable documents receive a candidate only after explicit user confirmation.
Each field carries its own readiness label: ready, weak, or weak-but-explicit (weak, and the user agreed to leave it unresolved). Only the user sets weak-but-explicit. Requirements are converged when every applicable field is ready or weak-but-explicit.
Judgment rules per field: references/criteria.md.
Hearing Protocol
Use the available scope and cost evidence for both elicitation and judgment, then ask only for product choices that the repository cannot answer. Repeat scope and cost analysis only when an answer changes the analysis target or required scope evidence.
Register these steps before starting and record each step's evidence as it completes:
| Step | Action | Completion evidence |
|---|---|---|
| 1 | State the available scope facts, then separately what they imply for the requirement | Facts listed with their analysis evidence |
| 2 | Ask about the fields below ready, at most two questions per message |
One question per field below ready |
| 3 | Record each answer as that field's value | The value is the option the user selected or the wording the user supplied |
| 4 | Re-ask once when a recorded value still fails its pass condition, then mark the field weak-but-explicit when the user agrees to leave the second answer as it stands |
Two recorded answers, or the user's agreement to stop |
| 5 | Judge each field against its pass condition and finalize the completed record | A convergence record with every field labeled |
What ships with it
1 file 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.
- 4d ago Changed 2584cf0ddfe4
- 9d ago First seen · 70 lines · 67 tokens per session scan A 7a7c758d6449
requirement-convergence is a skill published in the GitHub repository shinpr/ai-coding-project-boilerplate (228 stars, last pushed 3d ago), licensed MIT. It adds 67 tokens to every session and 937 once invoked, about $0.0003 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.
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