Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/jubscodes/get-shit-prettynpx agentmods add skills/jubscodes/get-shit-pretty/gspdev-prompt-auditWrote 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/jubscodes/get-shit-pretty/gspdev-prompt-audit)<a href="https://agentmods.dev/skills/jubscodes/get-shit-pretty/gspdev-prompt-audit"><img src="https://agentmods.dev/badge/skills/jubscodes/get-shit-pretty/gspdev-prompt-audit/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/jubscodes/get-shit-pretty/gspdev-prompt-audit"><img src="https://agentmods.dev/badge/skills/jubscodes/get-shit-pretty/gspdev-prompt-audit.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 | $0.00040 | $0.01576 |
| Opus 5 | $0.00020 | $0.00788 |
| Sonnet 5 | $0.00008 | $0.00315 |
| Haiku 4.5 | $0.00004 | $0.00158 |
Grade A, and why
gspdev-prompt-audit 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 10d 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 — 187 lines — stays where its author put it; the contents beside it link to each section on GitHub.
This skill performs semantic analysis that automated tests (P1–P7 in audit-tests.sh) can't catch. It evaluates meaning, not just structure.
Principle: "Your AI setup should be getting simpler over time — addition by subtraction."
Source layout:
gsp/skills/*/SKILL.md— 34 skillsgsp/agents/gsp-*.md— 15 agents
Step 1: Parse scope
$ARGUMENTS determines what to analyze:
allor empty — analyze everything (skills → agents → cross-file)skills— skills onlyagents— agents only- specific name (e.g.
gsp-project-designer) — analyze that one file + its paired skill/agent
Step 2: Run automated baseline first
bash dev/scripts/audit-tests.sh prompts
Note the warnings — they provide structural context for the semantic analysis.
Step 3: Per-file semantic analysis
For each file in scope, read it fully and evaluate against these 5 criteria:
3a: Dead weight
Instructions the model already follows without being told. Examples:
- "Write clean, maintainable code" — Claude does this by default
- "Be helpful and thorough" — core model behavior
- "Follow best practices" — too vague to add value
- "Ensure high quality output" — the model always tries to
Test: Would removing this instruction change the output? If no → dead weight.
3b: Contradictions
Rules that conflict within the same file or between a skill and its spawned agent. Examples:
- "Be concise" + "Explain every decision in detail"
- "Use bullet points" + later requiring paragraph-format output
- Skill says "keep output under 100 lines" but agent says "be thorough and complete"
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.
- 10d ago First seen · 187 lines · 40 tokens per session scan A b22b5f8e0211
gspdev-prompt-audit is a skill published in the GitHub repository jubscodes/get-shit-pretty (54 stars, last pushed 3mo ago), licensed MIT. It adds 40 tokens to every session and 1,576 once invoked, about $0.0002 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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