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 terrylica/cc-skills --skill analyzegit clone --depth 1 https://github.com/terrylica/cc-skillsWrote 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/terrylica/cc-skills/analyze)<a href="https://agentmods.dev/skills/terrylica/cc-skills/analyze"><img src="https://agentmods.dev/badge/skills/terrylica/cc-skills/analyze/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/terrylica/cc-skills/analyze"><img src="https://agentmods.dev/badge/skills/terrylica/cc-skills/analyze.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Rogue Agent · line 79 Skill modifies its own code, configuration, or behavior at runtime. Self-modification enables an agent to escalate privileges, disable safety constraints, or install persistent backdoors.Fix: Prevent the skill from modifying its own code, SKILL.md, or configuration files. Treat skill files as read-only at runtime.
- medium Excessive Agency · line 36 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00023 | $0.00789 |
| Opus 5 | $0.00012 | $0.00394 |
| Sonnet 5 | $0.00005 | $0.00158 |
| Haiku 4.5 | $0.00002 | $0.00079 |
Grade A, and why
analyze 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 — 82 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/asciinema-tools:analyze
Run semantic analysis on converted .txt recordings.
Self-Evolving Skill: This skill improves through use. If instructions are wrong, parameters drifted, or a workaround was needed — fix this file immediately, don't defer. Only update for real, reproducible issues.
Arguments
| Argument | Description |
|---|---|
file |
Path to .txt file |
-d, --domains |
Domains: trading,ml,dev,claude |
-t, --type |
Type: curated, auto, full, density |
--json |
Output in JSON format |
--md |
Save as markdown report |
--density |
Include density analysis |
--jump |
Jump to peak section after analysis |
Execution
Invoke the asciinema-analyzer skill with user-selected options.
Skip Logic
- If
fileprovided -> skip Phase 1 (file selection) - If
-tprovided -> skip Phase 2 (analysis type) - If
-dprovided -> skip Phase 3 (domain selection) - If
--json/--mdprovided -> skip Phase 6 (report format) - If
--jumpprovided -> auto-execute jump after analysis
Workflow
- Preflight: Check for .txt file
- Discovery: Find .txt files
- Selection: AskUserQuestion for file
- Type: AskUserQuestion for analysis type
- Domain: AskUserQuestion for domains (multi-select)
- Curated: Run ripgrep searches
- Auto: Run YAKE if selected
- Density: Calculate density windows if selected
- Format: AskUserQuestion for report format
- Next: AskUserQuestion for follow-up action
Examples
# Quick curated analysis for trading domain
/asciinema-tools:analyze session.txt -d trading -t curated
# Full analysis with density and JSON output
/asciinema-tools:analyze session.txt -t full --density --json
# Auto keyword discovery with markdown report
/asciinema-tools:analyze session.txt -t auto --md
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.
- 9d ago First seen · 82 lines · 23 tokens per session scan A a8c4ca723916
analyze is a skill published in the GitHub repository terrylica/cc-skills (66 stars, last pushed today), licensed MIT. It adds 23 tokens to every session and 789 once invoked, about $0.0001 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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