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 theshubh007/agent-skill-finder --skill grill-megit clone --depth 1 https://github.com/theshubh007/agent-skill-finderWrote 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/theshubh007/agent-skill-finder/grill-me)<a href="https://agentmods.dev/skills/theshubh007/agent-skill-finder/grill-me"><img src="https://agentmods.dev/badge/skills/theshubh007/agent-skill-finder/grill-me/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/theshubh007/agent-skill-finder/grill-me"><img src="https://agentmods.dev/badge/skills/theshubh007/agent-skill-finder/grill-me.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 | $0.00067 | $0.00434 |
| Opus 5 | $0.00034 | $0.00217 |
| Sonnet 5 | $0.00013 | $0.00087 |
| Haiku 4.5 | $0.00007 | $0.00043 |
Grade A, and why
Design Interrogation Mode 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 12d 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.
What it actually says
Behavior
Conduct a thorough, sequential interview covering every significant aspect of the submitted plan or design. Walk down each branch of the decision tree, resolving inter-dependencies between decisions one at a time.
Rules:
- Ask exactly one question per turn — no batching
- For each question, provide your own recommended answer with rationale
- If a question can be answered by inspecting the codebase, inspect it first rather than asking
- Do not stop until all decision branches are resolved and shared understanding is confirmed
Process
- Identify the top-level decisions and unknowns in the plan
- Prioritize by dependency order — foundational decisions first
- For each decision point:
- State the question clearly
- Provide your recommended answer and brief reasoning
- Wait for user confirmation or correction before proceeding
- After resolving a branch, summarize the agreed decision before moving to the next
- Conclude with a full decision summary once all branches are resolved
When to Use
- Pre-implementation architecture review
- Validating assumptions before a large feature build
- Identifying gaps or contradictions in a technical proposal
- Stress-testing a plan against edge cases and failure modes
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.
- 12d ago First seen · 56 lines · 67 tokens per session scan A cc72972fae55
Design Interrogation Mode is a skill published in the GitHub repository theshubh007/agent-skill-finder (13 stars, last pushed 4mo ago), licensed MIT. It adds 67 tokens to every session and 434 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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