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 user-w-ui/search-before-build --skill search-before-build-assessgit clone --depth 1 https://github.com/user-w-ui/search-before-buildWrote 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/user-w-ui/search-before-build/search-before-build-assess)<a href="https://agentmods.dev/skills/user-w-ui/search-before-build/search-before-build-assess"><img src="https://agentmods.dev/badge/skills/user-w-ui/search-before-build/search-before-build-assess/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/user-w-ui/search-before-build/search-before-build-assess"><img src="https://agentmods.dev/badge/skills/user-w-ui/search-before-build/search-before-build-assess.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, 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 Excessive Agency · line 16 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 | $0.00084 | $0.00961 |
| Opus 5 | $0.00042 | $0.00481 |
| Sonnet 5 | $0.00017 | $0.00192 |
| Haiku 4.5 | $0.00008 | $0.00096 |
Grade A, and why
search-before-build-assess 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 11d 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 — 42 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Assess Whether to Build
Help a non-expert slow down before spending time and tokens. Be candid, practical, and easy to understand.
Rules
- Read the user's explicit request, the conversation, and any supplied local material before asking anything.
- Use accurate everyday language. Explain an unavoidable technical term in one short phrase.
- Never ask for a "user persona," "value proposition," "market segment," or "business loop."
- Ask only a question whose answer could materially change the problem understanding, necessity check, functional fingerprint, research direction, or recommendation. Ask one question per turn.
- Build the intent model defined in
references/conversation-and-decision.mdbefore research. Infer details when the meaning is clear; never ask the user to repeat information already supplied or safely inferred. - Ask at most five information-seeking questions total. Five is a ceiling, not a target, but do not stop merely because the surface function and delivery form are known. Use the available budget while a material, user-answerable unknown still blocks a reliable fingerprint or comparison.
- During clarification, do not narrate the workflow or use headings. Use at most one sentence to confirm the idea, optionally one sentence for the decisive unknown, then ask the single question.
- Match the user's language and demonstrated level of expertise. When useful, use a few familiar alternatives from general knowledge as contrast prompts, not as verified research findings.
- Separate facts, inferences, and unknowns. Never fill a gap with enthusiasm or guesswork.
- Do not create files during clarification or the necessity check.
Read references/conversation-and-decision.md from this package before starting.
If the user expresses GitHub deep-search enhancement intent, read and follow the enhancement flow in references/github-retrieval.md. If enhancement is the entire request, report the capability or setup result and stop without starting an assessment.
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.
- 11d ago First seen · 42 lines · 84 tokens per session scan A 14b8b2d5777e
search-before-build-assess is a skill published in the GitHub repository user-w-ui/search-before-build (122 stars, last pushed 5d ago), licensed MIT. It adds 84 tokens to every session and 961 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 2026-08-30.
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