deepagents-code
Skill445 starsChanged 10 days agoMITView on GitHub
Analyze Deep Agents Code releases against LangChain Deep Agents Code docs and prepare one-feature documentation updates.
In this repository25 other files it gives its agents.
- AGENTS.mdAGENTS.md
- .github/copilot-instructions.mdCopilot instructions
- .cursor/rules/docs-style.mdcCursor rule
- add-docs-pageSkill
- docs-code-samplesSkill
- docs-editSkill
- docs-restructureSkill
- docs-reviewSkill
- docs-team-voiceSkill
- docs-tooling-notionSkill
- submit-integrationSkill
- update-integrations-prsSkill
- verify-against-sourceSkill
- deepagentsjsSkill
- deepagentsSkill
- openwikiSkill
- release-researchSkill
- ship-docs-updateSkill
- langgraph-docsSkill
- write-timestampSkill
- pandas-patternsSkill
- deep-agentsSkill
- langchainSkill
- langgraphSkill
- langsmithSkill
The file
We split this skill into the rules it gives an agent
8 rules. About 0 are common, 1 is distinctive, and 7 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈1
Distinctive · estimate
This author's own choices. Worth a look.
7
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 8
Use this skill when the product is Deep Agents Code (Products and setup → Deep Agents Code).
- Very specific: line 39
When unsure, open a small clarifying ticket/PR only if a reader of the current docs would be misled.
- Very specific: line 45
After research returns features with needs_docs: true, read /memories/agent/deepagents-code-releases.md and skip any already recorded for …
- Very specific: line 46
Call get_docs_file on AGENTS.md and read it in full.
- Very specific: line 49
Prefer updating the owning page over creating a new page.
- Very specific: line 51
After shipping, append the release tag, feature name, Linear URL, and PR URL to /memories/agent/deepagents-code-releases.md.
- Very specific: line 52
Keep /memories/agent/AGENTS.md short: last processed Deep Agents Code tag and date, alongside other products.
- Very specific: line 56
Use cold memory file /memories/agent/deepagents-code-releases.md:
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Deep Agents Code docs release skill
Use this skill when the product is Deep Agents Code (Products and setup → Deep Agents Code). Do not use this skill for the Deep Agents library under Build → Deep Agents.
Sources of truth
- Releases: GitHub
langchain-ai/deepagentsviaget_eligible_release/get_release_notes - Important: that repo publishes several packages. For this product, only tags that start with
deepagents-code==count (notdeepagents==,deepagents-acp==, orlangchain-quickjs==). - Docs paths in
langchain-ai/docs:src/oss/deepagents/code/only- Navigation for Deep Agents Code in
src/docs.json - Docs style authority: root
AGENTS.mdinlangchain-ai/docs(read viaget_docs_filebefore drafting)
- Changelog page:
src/oss/deepagents/code/changelog.mdx(points at the upstream code changelog)
Deep Agents Code pages are unversioned (no Python/TypeScript language split). Conditional fences still resolve against the Python branch.
What usually needs docs
Prioritize user-facing changes:
- New CLI commands, flags, config keys, or slash commands
- New providers, plugins, hooks, MCP wiring, or credential flows
- Approval modes, subagents, sandboxes, or remote sandbox behavior
- Behavior changes that make existing docs wrong
- New minimum versions that docs should call out
Usually skip docs for:
- Internal refactors with no user-visible change
- Dependency bumps with no behavior change
- Pure bug fixes that do not change documented behavior
- Changes that belong only to the Deep Agents library (
deepagents==...releases)
When unsure, open a small clarifying ticket/PR only if a reader of the current docs would be misled.
Workflow for one Deep Agents Code release
The main agent must run phase 1 through the release-research subagent first (diff + source investigation). This skill guides phase 2 shipping and judgment details the subagent also uses.
- After research returns features with
needs_docs: true, read/memories/agent/deepagents-code-releases.mdand skip any already recorded for that tag. - Call
get_docs_fileonAGENTS.mdand read it in full. Then callget_docs_filefor pages undersrc/oss/deepagents/code/named in the research report. - For each remaining feature:
- Edit surgically from the page
get_docs_filecontent, following the docs repoAGENTS.md. - Prefer updating the owning page over creating a new page. If a new page is required, also plan the
src/docs.jsonnavigation update under Deep Agents Code. - Load the
ship-docs-updateskill and ship that feature alone with the research report'sevidenceasevidence_json.
- Edit surgically from the page
- After shipping, append the release tag, feature name, Linear URL, and PR URL to
/memories/agent/deepagents-code-releases.md. - Keep
/memories/agent/AGENTS.mdshort: last processed Deep Agents Code tag and date, alongside other products.
Memory format
Use cold memory file /memories/agent/deepagents-code-releases.md:
# Deep Agents Code release tracking
## deepagents-code==0.1.84
- feature: remote sandboxes config
- linear: https://linear.app/...
- pr: https://github.com/langchain-ai/docs/pull/...Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

