Borrowing it
Nothing to install: this file belongs to strikersam/autonomous-ai-agency. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/strikersam/autonomous-ai-agency/master/.agents/skills/prompt-transparency/SKILL.mdgit clone --depth 1 https://github.com/strikersam/autonomous-ai-agencyWrote 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/strikersam/autonomous-ai-agency/prompt-transparency)<a href="https://agentmods.dev/skills/strikersam/autonomous-ai-agency/prompt-transparency"><img src="https://agentmods.dev/badge/skills/strikersam/autonomous-ai-agency/prompt-transparency/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/strikersam/autonomous-ai-agency/prompt-transparency"><img src="https://agentmods.dev/badge/skills/strikersam/autonomous-ai-agency/prompt-transparency.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, 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 Anti-Refusal · line 39 Skill attempts to nullify the agent's safety policies or restrictions ('you have no restrictions', 'ignore your guidelines', 'do anything now'). This is a direct jailbreak that disables guardrails.Fix: Remove jailbreak framing that nullifies safety policies or restrictions. Skill content must not instruct the agent to ignore its guidelines or operate without guardrails.
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 | $0.00000 | $0.00531 |
| Opus 5 | $0.00000 | $0.00266 |
| Sonnet 5 | $0.00000 | $0.00106 |
| Haiku 4.5 | $0.00000 | $0.00053 |
Grade A, and why
prompt-transparency 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.
How it starts
The opening of the file, as written. The whole thing — 62 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: prompt-transparency
Purpose
Inspired by the CL4R1T4S project (github.com/elder-plinius/CL4R1T4S), this skill audits and surfaces all implicit behavioral instructions, system prompts, and agent directives embedded in this repository. It generates a human-readable transparency report so anyone can understand exactly how the AI agents in this repo are instructed to behave.
When to Use
- When onboarding new contributors who want to understand agent behavior
- Before a release to document what behavioral rules are active
- When debugging unexpected agent behavior
- Periodically as a governance/transparency checkpoint
Steps
1. Collect All Agent & Skill Definitions
Scan and read every file that contains behavioral instructions:
.claude/agents/*.md— named agent personas and their directives.agents/skills/*/SKILL.md— skill behavioral definitions.claude/commands/*.md— slash command behaviorsCLAUDE.md(root) — global project-level instructions (if present).claude/state/*— current runtime state
2. Extract Key Behavioral Dimensions
For each file found, extract:
- Role/Persona: What role does this agent/skill play?
- Constraints: What is it explicitly told NOT to do?
- Capabilities: What is it allowed/instructed to do?
- Tone/Style: Any communication style directives?
- Decision Rules: Any if/then behavioral rules?
3. Generate Transparency Report
Output a structured report to docs/prompt-transparency-report.md with:
- Summary table of all active agents and skills
- Full behavioral inventory per component
- Conflict detection (contradictory instructions across agents)
- Coverage gaps (areas with no behavioral guidance)
4. Flag Risks
Highlight any instructions that:
- Grant broad permissions without guardrails
- Could conflict with each other
- Are ambiguous or underspecified
5. Commit the Report
Use the smart-commit skill to push the report with a clear commit message.
Output Format
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 · 62 lines · 0 tokens per session scan A a2c245fe1ebc
prompt-transparency is a skill published in the GitHub repository strikersam/autonomous-ai-agency (8 stars, last pushed today), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 531 tokens. 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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