Borrowing it
Nothing to install: this file belongs to warpdotdev/common-skills. 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/warpdotdev/common-skills/main/.agents/skills/readout/SKILL.mdgit clone --depth 1 https://github.com/warpdotdev/common-skillsWrote 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/warpdotdev/common-skills/readout)<a href="https://agentmods.dev/skills/warpdotdev/common-skills/readout"><img src="https://agentmods.dev/badge/skills/warpdotdev/common-skills/readout/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/warpdotdev/common-skills/readout"><img src="https://agentmods.dev/badge/skills/warpdotdev/common-skills/readout.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- 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 Rogue Agent · line 3 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
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 | $0.00137 | $0.01676 |
| Opus 5.5 | $0.00055 | $0.00670 |
| Sonnet 5.5 | $0.00027 | $0.00335 |
| Haiku 4.5 | $0.00014 | $0.00168 |
Grade A, and why
readout 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 2mo 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 — 104 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Readout
A readout turns an investigation into a durable HTML document someone can read weeks later without any of the original context. It starts one of two ways:
- Snapshot mode — invoked mid-conversation ("write this up"): the conversation's accumulated findings are the source material.
- Research mode — invoked fresh ("/readout on how github webhook events are processed in the server"): there is no conversation to mine, so the investigation itself is part of the job.
Either way, invoking this skill is a side task. Your job as the main agent is to sharpen the scope, launch a child agent with a good brief, and get out of the way — the child does the mining/research and the writing, keeping that (often large) work out of your context window.
Orchestrator workflow
1. Sharpen the scope — ask before launching
A vague brief produces a vague document. Before launching you should be able to list the specific questions the document will answer; if you can't, interview the user first:
- Ask 2–4 targeted questions, offering concrete options rather than open prompts — take a quick look at the code or topic first so the options are real (subsystems, entry points, competing concerns). For "/readout on how github webhook events are processed": which direction matters — inbound triggers, post-back, or both? a current-state reference or a gotcha hunt? which repo(s)?
- Always pin down depth and audience: high-level orientation vs. deep mechanics with line-level grounding; personal notes vs. shared with the team.
- Respect a shrug. "Just a high-level overview" is a valid answer — record it in the brief and move on rather than interrogating. Even then, try to extract the two or three questions the reader most needs answered; specificity is what makes a readout useful.
- Skip the interview when the scope is already specific — a snapshot of a focused conversation, or a precise research request, needs no questions. In snapshot mode the conversation usually supplies the questions; ask only when the invocation is ambiguous about which threads to include.
What ships with it
5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 2mo ago First seen · 104 lines · 137 tokens per session scan A e334d9e761b2
readout is a skill published in the GitHub repository warpdotdev/common-skills (636 stars, last pushed yesterday), licensed MIT. It adds 137 tokens to every session and 1,676 once invoked, about $0.0005 per session on Opus 5.5. 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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