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 Goktug/ai-crew --skill intake-with-validationgit clone --depth 1 https://github.com/Goktug/ai-crewWrote 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/goktug/ai-crew/intake-with-validation)<a href="https://agentmods.dev/skills/goktug/ai-crew/intake-with-validation"><img src="https://agentmods.dev/badge/skills/goktug/ai-crew/intake-with-validation/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/goktug/ai-crew/intake-with-validation"><img src="https://agentmods.dev/badge/skills/goktug/ai-crew/intake-with-validation.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 | $0.00060 | $0.03450 |
| Opus 5 | $0.00030 | $0.01725 |
| Sonnet 5 | $0.00012 | $0.00690 |
| Haiku 4.5 | $0.00006 | $0.00345 |
Grade A, and why
intake-with-validation 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 — 266 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Intake with Validation
Overview
Run structured Q&A one question at a time, even when the request seems crystal clear. The most expensive bugs in a team-lead run come from assumptions the team-lead filled in silently during intake. This skill extracts what the user actually wants — not what they think they should want — and captures scope, success criteria, hard constraints, and non-goals directly in spec.md. No separate intake artifact, no batched questions, no skipping steps because "the user obviously meant X."
When to Use
- The team-lead is starting Phase 1 (Intake) of a new run.
- The user invoked
/team-leadwith any new request — clear, vague, big, or small. - A new requirement appeared mid-run that wasn't covered in the original
spec.md.
When NOT to use:
- A pure code-review or read-only investigation that won't write code or open a PR.
- Continuation of an in-progress run where intake has already happened.
The Process
Step 1 — Hypothesize, with a confidence number
Before asking anything, write down your current best read of what the user actually wants in one sentence, plus an honest confidence number (0–100%). Below ~70%, append a — missing: <what's still unresolved> tail on the same line:
HYPOTHESIS: You want to reduce p99 latency on /pricing by caching responses.
CONFIDENCE: ~25% — missing: actual pain (latency vs. cost vs. rate limit), cache scope, invalidation triggers.
HYPOTHESIS: You want to jitter the midnight cron so it doesn't all fire at 00:00:00.
CONFIDENCE: ~90%
The number forces honesty. If you wrote a high number but can't predict the user's reactions to the next three questions you'd ask (see The 95% confidence stop below), the number is wrong. Start at the confidence level you can defend.
The — missing: tail tells the user exactly what intake needs to surface and prevents the number from being a vague signal.
Step 2 — Ask one question at a time, each with a GUESS attached
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 · 266 lines · 60 tokens per session scan A 213bd22634eb
intake-with-validation is a skill published in the GitHub repository Goktug/ai-crew (6 stars, last pushed 1mo ago), licensed MIT. It adds 60 tokens to every session and 3,450 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 2026-08-31.
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