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 MichaelYcJo/SpecSeal --skill confidence-checkgit clone --depth 1 https://github.com/MichaelYcJo/SpecSealWrote 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/michaelycjo/specseal/confidence-check)<a href="https://agentmods.dev/skills/michaelycjo/specseal/confidence-check"><img src="https://agentmods.dev/badge/skills/michaelycjo/specseal/confidence-check/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/michaelycjo/specseal/confidence-check"><img src="https://agentmods.dev/badge/skills/michaelycjo/specseal/confidence-check.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 | $0.00133 | $0.00683 |
| Opus 5.5 | $0.00053 | $0.00273 |
| Sonnet 5.5 | $0.00027 | $0.00137 |
| Haiku 4.5 | $0.00013 | $0.00068 |
Grade A, and why
confidence-check 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 7d 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 — 79 lines — stays where its author put it; the contents beside it link to each section on GitHub.
confidence-check, is the ground under this actually known?
Three things get assumed at the start of implementation and are wrong often enough to be worth a minute: that nothing equivalent already exists, that the API is as remembered, and that the bug's cause is understood rather than guessed. Settle them before writing, not after.
Five checks
-
No duplicate exists
- Search codebase for similar functionality
- Check if existing code can be extended instead
-
Architecture compliant
- Uses existing stack and patterns in the project
- No unnecessary new dependencies
- Follows project's established conventions
-
Official docs reviewed
- Library or framework API verified against current version
- Breaking changes checked if upgrading
-
Working reference found
- OSS example or proven pattern identified
- Not relying on untested approach
-
Root cause understood
- For bugs: clear understanding of WHY it fails
- For features: clear understanding of requirements
What to do with the answers
Where any check is unsatisfied, say which, and ask. Where all five are satisfied, proceed. That is the whole rule, and it is why no score is kept: a single miss is the whole answer, so a percentage carries nothing the list of unsatisfied checks does not, while looking like a measurement.
A number also invites the wrong move. It can be nudged: one check called "partial" instead of "failed" lifts a total past a threshold, and nothing in the report shows that happened. A named unsatisfied check cannot be nudged; it is either answered or still open.
An unsatisfied check is not a reason to stop. It is a thing to say out loud before writing code, so the person who can settle it gets the chance. Most are settled in one exchange.
Output format
Ready: <checks satisfied, one line each>
Not ready: <check>: <what is missing, and what would settle it>
Unknowable here: <check>: <who can answer>
<Proceeding, or Asking first>, because <the one sentence that follows from above>.
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.
- 7d ago Changed · -1 lines · +5 tokens per session 013c772fc65b
- 1mo ago Changed · +1 tokens per session dc082bb4599b
- 2mo ago First seen · 80 lines · 127 tokens per session scan A 70d18adcf0d7
confidence-check is a skill published in the GitHub repository MichaelYcJo/SpecSeal (1 stars, last pushed 4d ago), licensed MIT. It adds 133 tokens to every session and 683 once invoked, about $0.0005 per session on Opus 5.5. 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.
Other skills, from other repositories
critical-code-reviewer
Rigorously review code or pull requests for correctness, security, accessibility, maintainability, tests, and edge cases. Use when users request a critical code review, want a guided walkthrough of findings, need implementer-facing feedback, or want to prepare, create, or submit a GitHub pull request review.
brooks-sweep
Full-sweep mode: runs a unified analysis across all quality dimensions — code decay, architecture, tech debt, and test quality — then applies fixes directly to the codebase. Safe changes are auto-applied; risky changes are confirmed before execution. Drawing on twelve classic engineering books. Triggers when: user…
pr-review
Comprehensive PR review across six dimensions — cost impact, environment drift, ownership gaps, SOC 2 compliance, deprecated API / version hygiene, and rollback feasibility. Each mode inspects the diff and current file state, reports findings with severity, and recommends concrete fixes. Use when preparing a PR for…
pr-review
Use when the user wants to deeply review a pull/merge request or a local diff — "review this PR", "grill the MR", "stress-test this diff", "deep-dive code review", "code review before merge", or when they name a PR/MR URL, number, branch, commit range (A..B/A...B), tag or SHA. Works on GitHub (gh), GitLab (glab), or a…
genshijin-review
A compact pull-request review format that writes one actionable finding per line in Japanese or English.
skill-distiller
Fetches top-rated skills from skills.sh, analyzes them, and synthesizes one token-efficient skill combining the best elements. Use when the user asks to "distill skills for X", "find and combine skills for X", "synthesize skills", "merge skills", "make a skill for X from skills.sh", "update distilled skill", or…