LangChainKnown publisherlangchain-ai/docs/src/code-samples/deepagents/skills/write-timestamp/SKILL.mdwrite-timestamp
Skill445 starsChanged 10 days agoMITView on GitHub
Use when the user wants the current date and time written to a file via the bundled script inside the sandbox.
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
- deepagents-codeSkill
- deepagentsjsSkill
- deepagentsSkill
- openwikiSkill
- release-researchSkill
- ship-docs-updateSkill
- langgraph-docsSkill
- pandas-patternsSkill
- deep-agentsSkill
- langchainSkill
- langgraphSkill
- langsmithSkill
The file
We split this skill into the rules it gives an agent
2 rules. About 0 are common, 0 are distinctive, and 2 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈0
Distinctive · estimate
This author's own choices. Worth a look.
2
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 11
Run it with the execute tool, for example: python /skills/write-timestamp/write_timestamp.py
- Very specific: line 12
Read /tmp/skill_timestamp.txt with read_file and summarize the result for the user.
≈ “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
Write timestamp
Instructions
- The script is available in the sandbox at
/skills/write-timestamp/write_timestamp.pyafter sync. - Run it with the
executetool, for example:python /skills/write-timestamp/write_timestamp.py - Read
/tmp/skill_timestamp.txtwithread_fileand summarize the result for the user.
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.