Agent skill

Readout

by warpdotdev in warpdotdev/common-skills

Produce a polished, self-contained HTML "readout" document under ~/.readouts (with an auto-maintained index page), either by snapshotting the findings accumulated in the current conversation or —…

MITAuto-check passedAgent Workflows

Install Readout

skills CLI
$ npx skills add warpdotdev/common-skills --skill readout -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install warpdotdev/common-skills readout --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/warpdotdev/common-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/readout .claude/skills/readout && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
readout
GitHub stars
606
Token cost
~2k tokens
SKILL.md length
722 words
Files
6 (incl. scripts, references, assets)
Skills in repo
28
Repo updated
First seen
Licence
MIT

At a glance

Produce a polished, self-contained HTML "readout" document under ~/.readouts (with an auto-maintained index page), either by snapshotting the findings accumulated in the current conversation or —…

  • Works in 4 steps: Sharpen the scope — ask before launching → Compose the brief → Launch one local child agent → …
  • The user invokes /readout
  • SKILL.md covers Orchestrator workflow, Child agent prompt template and Fallbacks
  • Runs Python scripts from its folder

What it does

Readout is an agent skill from warpdotdev/common-skills. Produce a polished, self-contained HTML "readout" document under ~/.readouts (with an auto-maintained index page), either by snapshotting the findings accumulated in the current conversation or — when invoked fresh, e.g. "/readout on how github webhook events are processed" — by sharpening scope with clarifying questions and researching the codebase before documenting. The work runs in a child agent so the main conversation's context stays clean. Use whenever the user invokes /readout, says "write this up", "turn…

Its SKILL.md is about 2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 8 other files, including scripts, reference files and assets (for example `references/doc-guide.md`, `scripts/embed_snippets.py` and `scripts/update_index.py`).

It sits in Agent Workflows, covering Webhooks and Requirements gathering. It works with GitHub. The licence is MIT.

When your agent uses it

  • The user invokes /readout
  • Says write this up
  • Turn this into a doc/page
  • Asks for a readable

Example prompts

  • “readout”
  • “/readout on how github webhook events are processed”
  • “s context stays clean. Use whenever the user invokes /readout, says”
  • “/readout”

Requirements

  • Python 3

Workflow steps

4 steps, taken from the step headings in SKILL.md.

  1. Sharpen the scope — ask before launching
  2. Compose the brief
  3. Launch one local child agent
  4. Get back to work

What it can do on your machine

Read from SKILL.md and the folder at commit 69b4753. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 2 files in scripts/ (Python), which the agent can run.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Readout loads about 2k tokens when it runs, and up to ~4.1k if it reads all its reference files. Until then it costs about 166 tokens; SKILL.md has 722 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~166
When it runs · the whole SKILL.md, loaded when a task matches
~2k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~4.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from warpdotdev/common-skills at commit 69b4753, republished under its MIT licence (© warpdotdev). 722 words, ~1,959 tokens.

Download SKILL.mdSave it as .claude/skills/readout/SKILL.md (or your agent's skills folder). This skill also uses 5 other files; get the full folder from GitHub.
name
readout
description
Produce a polished, self-contained HTML "readout" document under ~/.readouts (with an auto-maintained index page), either by snapshotting the findings accumulated in the current conversation or — when invoked fresh, e.g. "/readout on how github webhook events are processed" — by sharpening scope with clarifying questions and researching the codebase before documenting. The work runs in a child agent so the main conversation's context stays clean. Use whenever the user invokes /readout, says "write this up", "turn this into a doc/page", "make a readout", or asks for a readable, shareable document capturing findings or explaining how something works.

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.
2. Compose the brief

Write a short brief (roughly 10–20 lines) carrying pointers, not payloads:

  • A working title / topic, and the mode (snapshot or research)
  • The specific questions the document must answer (from the conversation or the interview), plus depth and audience
  • Scope: which threads/subsystems to cover, and anything to explicitly exclude
  • Snapshot mode: headline conclusions worth centering the doc on, one line each — the child pulls the full content from conversation history itself, so don't paste findings wholesale
  • Research mode: starting pointers — entry-point files, symbols, or directories you already know about
  • Absolute paths to the repos/directories that ground the work
  • Each repo's hosted URL and the examined commit when known (e.g. github.com/org/repo @ abc123), so the document can hyperlink code references
Show full SKILL.md (272 more words)Show less
3. Launch one local child agent

Spawn exactly one child agent via run_agents, local execution. Local matters: the document lands on the user's filesystem and opens in their browser. Name the child readout-<topic-slug>.

Build the child's prompt from the template below. It must include:

  • The brief
  • The source-material block matching the mode (snapshot mode also needs your agent run ID — current_run_id from the orchestration runtime context — so the child can mine the parent conversation with search_conversation_history)
  • The instruction to read references/doc-guide.md from this skill's directory before writing
  • The output path convention and completion protocol
4. Get back to work

After launching, resume whatever you were doing, or end your turn — the child's completion message arrives on its own; relay the file path to the user with a one-line description when it does. In research mode a fresh conversation may have nothing else pending; just end the turn. Don't sit in a wait loop unless the user asked to wait for the document.

Child agent prompt template

Adapt this; keep the structure, and include the source-material block that matches the mode.

You are producing a "readout": a single self-contained HTML document that answers a
specific set of questions about <topic>, for a reader who has none of this context.

Brief:
<brief — including the questions to answer, depth, and audience>

Source material (snapshot mode):
- The parent conversation: agent run ID <current_run_id>. Use search_conversation_history
  with agent_run_id set to that ID. Make several targeted queries — one per question in
  the brief — rather than one broad query; targeted queries surface far more usable detail.
- The codebase(s) at <absolute paths>. The conversation is your starting point, not a cage:
  verify file references before asserting them, and where a section needs more depth to
  stand on its own, go read the code and fill the gap.

Source material (research mode):
- Investigate directly in the codebase(s) at <absolute paths>. Let the brief's questions
  drive the investigation: trace the actual code paths, read the real implementations, and
  ground every claim in file:line references. Distinguish verified from inferred. Do not
  pad the document with generic knowledge — its value is what's true of THIS codebase.

- Repo host + commit for linked code references, if known: <github.com/org/repo @ commit>
  (otherwise derive from git; see the doc guide's "Linked code references").

Start from the canonical template at <skill-directory>/assets/template.html — its
data-readout chrome blocks must be copied verbatim so every readout looks like every
other. Before writing, read <skill-directory>/references/doc-guide.md and follow it.

Output:
- Write ONE self-contained HTML file to ~/.readouts/<YYYY-MM-DD>-<topic-slug>.html
  (create ~/.readouts if it doesn't exist; suffix -2, -3, ... if the name is taken;
  get the date from `date +%F`).
- Embed referenced source per the doc guide when a repo is checked out
  (<skill-directory>/scripts/embed_snippets.py).
- Refresh the readouts index: python3 <skill-directory>/scripts/update_index.py
  (fully regenerates ~/.readouts/index.html listing every readout).
- When the file is written, open it with `open <path>` (skip this if the environment is
  headless).
- Report back to your orchestrator: the absolute file path, a 2–3 sentence summary of what
  the document covers, and anything you could not verify.

Fallbacks

  • Child spawning unavailable or denied: produce the document yourself, following references/doc-guide.md. If a research subagent is available, delegate the conversation-mining or code investigation to it so your context still stays lean.
  • Child can't search conversation history (snapshot mode; it will report this back): reply to the child with a distilled dump of the findings so it can proceed — this is the one case where payload-in-prompt is the right call.
  • User-provided material instead of a conversation (transcripts, files, links): treat that material as the source; everything else in the workflow is unchanged.

© warpdotdev, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 5 other files (scripts, references, assets) in .agents/skills/readout of warpdotdev/common-skills.

  • SKILL.md
  • assets/code-pane.html
  • assets/template.html
  • references/doc-guide.md
  • scripts/embed_snippets.py
  • scripts/update_index.py

Open the folder on GitHubat commit 69b4753

Compare with similar skills

Readout next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Readout compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Readout this skillwarpdotdev/common-skills606—~2kAutomated safety check: PassMIT
Chat SDKdatabuddy-analytics/Databuddy1.2k—~2.6kAutomated safety check: PassAGPL-3.0
GitHub MCPvibeeval/vibecosystem531—~2.3kAutomated safety check: NotesMIT
Agentic Workflow Designerdotnet/Open-XML-SDK4.6k2 repos~3.5kAutomated safety check: PassMIT
DBS Skill Makerdontbesilent2025/dbskill10k—~1.2kAutomated safety check: PassCustom licence
Ask NavigatorYeachan-Heo/oh-my-claudecode40k—~4.1kAutomated safety check: PassMIT

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Works with

Questions about Readout

What does Readout do?

Produce a polished, self-contained HTML "readout" document under ~/.readouts (with an auto-maintained index page), either by snapshotting the findings accumulated in the current conversation or —…. Readout is an agent skill from warpdotdev/common-skills.g.

When should I use Readout?

Readout fits situations like: the user invokes /readout; says write this up; turn this into a doc/page; asks for a readable.

How do I install Readout in Claude Code?

Run `npx skills add warpdotdev/common-skills --skill readout -a claude-code`. Or copy the skill folder (.agents/skills/readout in warpdotdev/common-skills) into .claude/skills/readout in your project. Claude Code loads it when a task matches its description.

How do I install Readout in Codex?

Run `npx skills add warpdotdev/common-skills --skill readout -a codex`. Or copy the skill folder (.agents/skills/readout in warpdotdev/common-skills) into .agents/skills/readout in your project. Codex loads it when a task matches its description.

Can I use Readout in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add warpdotdev/common-skills --skill readout -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/readout, .gemini/skills/readout, .github/skills/readout and .opencode/skills/readout in your project.

What does Readout need to run?

Going by SKILL.md and its folder, Readout needs Python for the scripts in its folder. Our summary lists: Python 3.

Does Readout access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Readout safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Readout use?

Readout is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Readout use?

About 2k tokens (SKILL.md is roughly 7.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 2.1k tokens, read only when the agent opens those files.

What are the alternatives to Readout?

Skills that share tags, products or a category with Readout: Chat SDK (databuddy-analytics/Databuddy, 1.2k stars), GitHub MCP (vibeeval/vibecosystem, 531 stars), Agentic Workflow Designer (dotnet/Open-XML-SDK, 4.6k stars) and DBS Skill Maker (dontbesilent2025/dbskill, 10k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Readout?

warpdotdev (a GitHub organization) maintains it in warpdotdev/common-skills, which has 606 GitHub stars. The repository holds 28 skills in this directory. The repository was last updated on September 30, 2026.

Source: warpdotdev/common-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.