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 agentmods add skills/mathieu0905/skilllens/skillscope-analyzernpx skills add mathieu0905/skilllens --skill skillscope-analyzergit clone --depth 1 https://github.com/mathieu0905/skilllensWhat 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 | $0.00072 | $0.04413 |
| Opus 5 | $0.00036 | $0.02207 |
| Sonnet 5 | $0.00014 | $0.00883 |
| Haiku 4.5 | $0.00007 | $0.00441 |
Grade A, and why
skillscope-analyzer 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 2d 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 — 327 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SkillScope Analyzer
Purpose
Analyze the selected skill-use window only. Current chat or whole-machine history is out of scope unless an input file explicitly points to it.
SkillScope provides file paths for the selected skill, normalized skill units, normalized trace events, raw trace text, and output artifacts. Follow those files, not assumptions.
Required Workflow
- Read all paths named in the launch prompt.
- Read the selected
SKILL.mdand the normalized skill units. - Compile the skill into analysis IR: constraints, condition predicates, obligations, prohibitions, ordering rules, and output contracts.
- Start from
constraint-seed.jsonwhen present; review and refine it instead of re-deriving every line from scratch. - Write or update
constraints.jsonas soon as the constraint review is complete. - Write or update
skill-graph.jsonafter extracting constraints and before judging the full trace. - Compile the trace into
trace-facts.json: event facts, artifact facts, ordering facts, and final-output facts. - Read
native-verifier.jsonwhen the launch prompt provides it. Treat it as deterministic evidence for final-output/artifact contracts only. - Run path-sensitive coverage over the skill graph using trace facts plus native verifier facts.
- Update graph branch/path state after trace inspection.
- Append concise progress notes to
progress.mdafter each meaningful stage. - Write
findings.jsonwhen you have coverage judgments worth surfacing. - Keep this pass focused on analysis artifacts; SkillScope launches
skillscope-optimizerafterfindings.jsonis saved. - Finish with a human-readable report citing evidence event IDs and native verifier facts where used.
Program Analysis Model
Treat the selected SKILL.md as a small specification program and the selected trajectory as one execution trace of that program.
Use this compiler-style analysis pipeline:
- Skill front-end
- Parse Markdown headings as modules / basic blocks.
- Parse bullets, numbered items, tables, examples, and output schemas into fine-grained constraints.
- Classify constraints into
condition,obligation,prohibition,ordering,numeric_bound,command_contract,file_contract,evidence_requirement, andfinal_output_contract. - Also classify each constraint target as
final_output,artifact,process,tool_use,reporting, orunknown. - Classify whether each constraint is a hard contract, soft recommendation, or implementation hint. Treat illustrative/reference code internals as hints unless surrounding prose says they are mandatory.
- Keep precise source spans. If one sentence contains two obligations or an obligation plus a condition, split it.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 2d ago First seen · 327 lines · 72 tokens per session scan A 484bd52cc6fb
skillscope-analyzer is a skill published in the GitHub repository mathieu0905/skilllens (2 stars, last pushed 2mo ago), licensed MIT. It adds 72 tokens to every session and 4,413 once invoked, about $0.0004 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 2026-08-31.
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