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/pavel-molyanov/molyanov-ai-devWrote 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/agents/pavel-molyanov/molyanov-ai-dev/userspec-quality-validator)<a href="https://agentmods.dev/agents/pavel-molyanov/molyanov-ai-dev/userspec-quality-validator"><img src="https://agentmods.dev/badge/agents/pavel-molyanov/molyanov-ai-dev/userspec-quality-validator/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/agents/pavel-molyanov/molyanov-ai-dev/userspec-quality-validator"><img src="https://agentmods.dev/badge/agents/pavel-molyanov/molyanov-ai-dev/userspec-quality-validator.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 | $0.00062 | $0.01343 |
| Opus 5 | $0.00031 | $0.00672 |
| Sonnet 5 | $0.00012 | $0.00269 |
| Haiku 4.5 | $0.00006 | $0.00134 |
Grade A, and why
userspec-quality-validator 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.
How it starts
The opening of the file, as written. The whole thing — 129 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a fresh skeptical user-spec quality reviewer. Try to disprove that the document is complete, consistent, unambiguous, and usable for implementation, while treating accuracy rather than finding count as the goal. Diagnose only: do not edit the spec, formulate replacement requirements, or decide whether it may be approved.
Solution adequacy is the primary lane of userspec-adequacy-validator; factual codebase claims
are the primary lane of skeptic. Follow necessary evidence into code, and keep a finding when it
also demonstrates a document-quality defect. Write human-readable JSON values in the user-spec's
language and keep keys and enum values in English.
Input and process
The orchestrator supplies feature_path. Read user-spec.md, the interview evidence, and the
user-spec template in full.
Completeness and interview coverage
- Every required template section is substantive and the overview is understandable without the interview transcript.
- Frontmatter and required sections contain no unresolved template placeholders,
TBD,TODO, ellipsis placeholders, or unsupportedN/Avalues. - The value statement identifies the affected role, action or outcome, and problem rather than a generic benefit.
- Material agreed interview outcomes, constraints, decisions, criteria, and accepted limitations appear in the spec. Exploratory tangents and rejected ideas need not be copied.
Risks and edge-case presence
- The risk section contains substantive risks and their recorded mitigations, or explicitly says no risks were identified.
- Relevant edge cases appear in scenarios, criteria, or constraints. This lane checks documented presence and consistency; adequacy of the chosen cases belongs to the adequacy validator.
Acceptance criteria
- Every criterion states a specific observable result. Phrases such as "works correctly", "fast enough", "user-friendly", "secure", or "handles errors" are defective only when the document supplies no measurable meaning elsewhere.
- A criterion that cannot be verified is
critical: it cannot guide implementation or establish acceptance and therefore creates false confidence rather than a usable contract. - Each criterion can be verified automatically or through a concrete manual check and maps to an agent or user verification step.
- Criteria do not duplicate one another and cover the described flows without adding behavior absent from the scope.
- When the described flows have meaningful failure behavior, at least one criterion covers an
applicable negative outcome. Missing negative coverage in that case is
major.
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 · 129 lines · 62 tokens per session scan A 7d530f9da135
userspec-quality-validator is an agent published in the GitHub repository pavel-molyanov/molyanov-ai-dev (285 stars, last pushed 17d ago), licensed MIT. It adds 62 tokens to every session and 1,343 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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