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 laurigates/claude-plugins --skill confidence-scoringgit clone --depth 1 https://github.com/laurigates/claude-pluginsWrote 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/laurigates/claude-plugins/confidence-scoring)<a href="https://agentmods.dev/skills/laurigates/claude-plugins/confidence-scoring"><img src="https://agentmods.dev/badge/skills/laurigates/claude-plugins/confidence-scoring/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/laurigates/claude-plugins/confidence-scoring"><img src="https://agentmods.dev/badge/skills/laurigates/claude-plugins/confidence-scoring.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00028 | $0.02229 |
| Opus 5.5 | $0.00011 | $0.00892 |
| Sonnet 5.5 | $0.00006 | $0.00446 |
| Haiku 4.5 | $0.00003 | $0.00223 |
Grade A, and why
confidence-scoring 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 9d 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 — 281 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Confidence Scoring for PRPs and Work-Orders
This skill provides systematic evaluation of PRPs (Product Requirement Prompts) and work-orders to determine their readiness for execution or delegation.
When to Use This Skill
| Use this skill when... | Use blueprint-prp-create instead when... |
|---|---|
| Scoring a draft PRP/work-order before execution or delegation | Authoring the PRP itself from research and context |
| Deciding whether a work-order is ready for a subagent or needs refinement | Producing the work-order content (use blueprint-work-order) |
| Reviewing existing PRPs/work-orders for context completeness and validation gates | Generating the PRD that the PRP derives from (use blueprint-derive-plans) |
Scoring Dimensions
1. Context Completeness (1-10)
Evaluates whether all necessary context is explicitly provided.
| Score | Criteria |
|---|---|
| 10 | All file paths explicit with line numbers, all code snippets included, library versions specified, integration points documented |
| 8-9 | Most context provided, minor gaps that can be inferred from codebase |
| 6-7 | Key context present but some discovery required |
| 4-5 | Significant context missing, will need exploration |
| 1-3 | Minimal context, extensive discovery needed |
Checklist:
- File paths are absolute or clearly relative to project root
- Code snippets include actual line numbers (e.g.,
src/auth.py:45-60) - Library versions are specified
- Integration points are documented
- Patterns from codebase are shown with examples
2. Implementation Clarity (1-10)
Evaluates how clear the implementation approach is.
| Score | Criteria |
|---|---|
| 10 | Pseudocode covers all cases, step-by-step clear, edge cases addressed |
| 8-9 | Main path clear, most edge cases covered |
| 6-7 | Implementation approach clear, some details need discovery |
| 4-5 | High-level only, significant ambiguity |
| 1-3 | Vague requirements, unclear approach |
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.
- 9d ago Changed 2fae7a62bb2c
- 1mo ago First seen · 281 lines · 28 tokens per session scan A 49e61de8b971
confidence-scoring is a skill published in the GitHub repository laurigates/claude-plugins (60 stars, last pushed yesterday), licensed MIT. It adds 28 tokens to every session and 2,229 once invoked, about $0.0001 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 2026-09-03.
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