Borrowing it
Nothing to install: this file belongs to vantage-sh/vantage-mcp-server. 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/vantage-sh/vantage-mcp-server/main/.agents/skills/writing-evals/SKILL.mdgit clone --depth 1 https://github.com/vantage-sh/vantage-mcp-serverWrote 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/vantage-sh/vantage-mcp-server/writing-evals)<a href="https://agentmods.dev/skills/vantage-sh/vantage-mcp-server/writing-evals"><img src="https://agentmods.dev/badge/skills/vantage-sh/vantage-mcp-server/writing-evals/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/vantage-sh/vantage-mcp-server/writing-evals"><img src="https://agentmods.dev/badge/skills/vantage-sh/vantage-mcp-server/writing-evals.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 7 findings, up to medium
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 →
- medium Agent Snooping · line 8 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
- medium Prompt Injection · line 27 Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
- medium Prompt Injection · line 34 Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
- medium Prompt Injection · line 36 Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
- medium Prompt Injection · line 37 Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
- medium System Prompt Leakage · line 133 Skill contains patterns that could indirectly extract system prompts through rephrasing, translation, summarization, or side-channel techniques.Fix: Guard against indirect extraction by refusing to summarize, translate, or rephrase system instructions. Add explicit anti-extraction clauses.
- medium Prompt Injection · line 158 Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
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 | $0.00060 | $0.03714 |
| Opus 5 | $0.00030 | $0.01857 |
| Sonnet 5 | $0.00012 | $0.00743 |
| Haiku 4.5 | $0.00006 | $0.00371 |
Grade A, and why
writing-evals 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 5d 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 — 188 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Writing evals
Unit tests prove a tool wires up and the API call shape is right. Evals prove the description + zod schema are good enough that a model can find and call the tool from a natural-language prompt. Tool authoring conventions (description style, zod .describe() strings) live in .agents/skills/writing-mcp-tools/SKILL.md; this skill covers the eval harness and how to iterate when rows fail.
Opt-in and execution approval
Evals are not a default part of adding or changing a tool. If the user has not already explicitly requested evals, ask whether they want them included. If they opt in, also ask whether the provider API key for the model they intend to use is configured in the ignored .env file. If they decline, do not add or modify eval case files, result JSON, or the generated site.
Opting in to eval authoring does not authorize running an eval. Model-backed evals make fresh API calls, may incur cost, and can create or replace result JSON. Unless the user explicitly asks to execute the eval:
- Write or update only the case file under
evals/cases/. - Do not run
npm run eval,npm run eval:all, or a filtered rerun. - Do not create or modify files under
evals/results/or regenerate the eval site as a consequence of the authoring task. - At handoff, provide the exact targeted command the user can run and mention
npm run eval -- --list-modelsfor the approved model catalog. You may also offer to run it, but wait for an explicit follow-up.
If the user wants evals but says the required key is not configured, author the case file only and explain the missing setup at handoff. If the user asks to run an eval but has not confirmed credential setup, ask whether the required provider key is configured in .env. If they have not selected a model, ask which approved model and effort they want before executing it. Explain that promptfoo loads credentials from .env and that every invocation makes fresh, uncached model calls. A repository requirement to produce a baseline before a PR is a pending verification step to report, not authorization to spend API credits.
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.
- 5d ago Changed · +7 lines 05ac3fa2a7d2
- 6d ago Changed 07042e52e309
- 11d ago First seen · 181 lines · 60 tokens per session scan A 9fdeedc8b385
writing-evals is a skill published in the GitHub repository vantage-sh/vantage-mcp-server (84 stars, last pushed today), licensed MIT. It adds 60 tokens to every session and 3,714 once invoked, about $0.0003 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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