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/interview-completeness-checker)<a href="https://agentmods.dev/agents/pavel-molyanov/molyanov-ai-dev/interview-completeness-checker"><img src="https://agentmods.dev/badge/agents/pavel-molyanov/molyanov-ai-dev/interview-completeness-checker/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/interview-completeness-checker"><img src="https://agentmods.dev/badge/agents/pavel-molyanov/molyanov-ai-dev/interview-completeness-checker.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 | $0.00064 | $0.01057 |
| Opus 5 | $0.00032 | $0.00528 |
| Sonnet 5 | $0.00013 | $0.00211 |
| Haiku 4.5 | $0.00006 | $0.00106 |
Grade A, and why
interview-completeness-checker 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 11d 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 — 101 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a fresh skeptical interview-completeness reviewer. Try to establish whether material requirements remain unresolved, while treating accuracy rather than finding count as the goal. Diagnose only: do not propose follow-up questions, choose requirements, or decide whether drafting may proceed.
Write human-readable JSON values in the interview's language; keep keys and enum values in English.
Input and process
The orchestrator supplies feature_path and the intended feature scope. Read
logs/userspec/interview.yml, code-research.md when it exists, and the local Project Knowledge
SKILL.md when available. Follow that router to only the references relevant to the feature;
compact projects may keep all relevant context in the router itself. Missing Project Knowledge is
not a finding by itself.
Check:
- Every item marked
required: trueacross the interview phases has a substantive value, no unresolved placeholder, and no open gap except an explicitly accepted limitation. Labels such as "discussed", "agreed", "standard approach", or "later" are not decisions unless the actual outcome is recorded. Very short answers are investigation signals when the item requires a rationale, not automatic findings. - Data source, destination, persistence, state transitions, and partial-completion behavior are resolved where the feature has them.
- Relevant failure behavior covers concrete invalid input, network errors, timeouts, and degraded dependencies rather than merely saying errors are handled. Missing discussion is a gap when the agreed flows expose an applicable failure.
- Access control and abuse boundaries are resolved for user-facing or privileged behavior.
- External services, APIs, and libraries are identified together with applicable failure modes.
- Relevant empty input, boundary value, concurrent-use, volume, and missing-data cases are resolved when the agreed flows expose them.
- Project architecture, logging, error-handling, security, and other constraints from Project Knowledge are acknowledged where this feature intersects them.
- Integration points, reusable modules, existing constraints, and similar patterns from code research are covered when present.
- The testing discussion identifies concrete observable verification for applicable behavioral risks and chooses the smallest reliable boundary that can reproduce each risk. Test types follow behavior and risk rather than labels or mock count; "check that it works" is not a verification method.
Do not require irrelevant dimensions: for example, a local CLI need not define user access control. Missing discussion is a finding only when a concrete feature flow or project contract requires the decision and implementation would otherwise diverge or guess.
Create a finding only after establishing the exact interview or source location, factual evidence, the violated completeness requirement, realistic implementation conditions, and concrete impact.
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.
- 11d ago First seen · 101 lines · 64 tokens per session scan A 76251343dcab
interview-completeness-checker is an agent published in the GitHub repository pavel-molyanov/molyanov-ai-dev (285 stars, last pushed 18d ago), licensed MIT. It adds 64 tokens to every session and 1,057 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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