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/baixinghao/intent-gate/requirement-alignmentnpx skills add baixinghao/intent-gate --skill requirement-alignmentgit clone --depth 1 https://github.com/baixinghao/intent-gateWrote 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/baixinghao/intent-gate/requirement-alignment)<a href="https://agentmods.dev/skills/baixinghao/intent-gate/requirement-alignment"><img src="https://agentmods.dev/badge/skills/baixinghao/intent-gate/requirement-alignment.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 | $0.00150 | $0.01310 |
| Opus 5 | $0.00075 | $0.00655 |
| Sonnet 5 | $0.00030 | $0.00262 |
| Haiku 4.5 | $0.00015 | $0.00131 |
Grade A, and why
requirement-alignment 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 — 104 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Requirement Intent Alignment
Overview
Ambiguity in a requirement is resolved through a funnel that gets cheaper per level, never by silent assumption. The MCP tools are the enforcement: they reject malformed questions, refuse to settle answers without a landing point, and gate delivery on mechanical lint.
The full law is the MCP prompt doc_analysis_playbook — read it in full before
starting Step 0. This skill is the map; the playbook is the territory.
Dual-layer detection — the diagram is the instrument, not a deliverable.
Layer 1 (reading): sweep the PRD text for explicit ambiguities (the nine-category
checklist). Layer 2 (drawing): do NOT wait for answers before drawing — hard-draw
draft diagrams in the FIRST turn; every node/edge you cannot draw becomes a TBDn
placeholder (state "???待确认" as TBDn / --> TBDn; never bare --> ???, lint's
state-id charset eats it). Each placeholder is a gap: 🔧 technical → code evidence
first, 📋 business → dispatch_question. Placeholders are cleared ONLY by code
evidence or a human ruling — never by guessing. The first resolve_question is
mechanically gated on the draft existing (analysis-draft.md with a mermaid block).
The Funnel
Resolve each gap at the cheapest level that can close it:
- Code evidence (🔧 technical gaps first) — search the codebase
(codegraph
search_graph/trace_path, or grep). If the code has a single ground truth, inject it and settle withresolve_question(source="code"). Zero human cost. - Registered inference — no direct ground truth but a strong analogy?
record_inferencewith an explicit evidence chain, batch-confirm with the human at session end viaconfirm_inferences. 🔴 Forbidden on core money flows and red-line rules — those need a human decision. - Group escalation (optional, sister intent-gate-service MCP) — judgment calls whose
rightful answerer sits in a DingTalk group: intent-gate-service's
group_dispatchwith category 📋 business / 🔧 technical, @ the right role. One question in flight at a time. Core-flow questions carry your inference as recommended option 1, so the human nods instead of drafting. Skip this level when intent-gate-service is not mounted. - Dialog fallback (default) — the host asks the user directly, 3+1 options per question.
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 First seen · 104 lines · 0 tokens per session scan A 17639c386c4a
requirement-alignment is a skill published in the GitHub repository baixinghao/intent-gate (2 stars, last pushed 20d ago), licensed MIT. It adds 150 tokens to every session and 1,310 once invoked, about $0.0007 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 2026-08-31.
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