gh-read-plan
Skill5 starsChanged 52 days agoMITView on GitHub
Read the GitHub plan issue given as argument. Use when the user tells you to "read this github plan issue" with the issue as argument.
In this repository7 other files it gives its agents.
- gh-close-planSkill
- gh-create-planSkill
- gh-create-prSkill
- gh-implement-planSkill
- gh-update-planSkill
- handoverSkill
- prompt-sessionSkill
The file
We split this skill into the rules it gives an agent
3 rules. About 0 are common, 2 are distinctive, and 1 is very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈2
Distinctive · estimate
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 8
Read the GitHub issue in $ARGUMENTS (issue URL or owner/repo#number) containing the detailed plan for the work that will be started or …
- Distinctive: line 10
When reading the issue, check both the body and comments for content.
- Distinctive: line 21
If a durable-memory CLI is configured, query it with the issue's distinctive terms after reading.
≈ “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
Read the GitHub issue in $ARGUMENTS (issue URL or owner/repo#number) containing the detailed plan for the work that will be started or continued in this conversation.
When reading the issue, check both the body and comments for content. Steps may be in a separate Steps comment (new format) or in the issue body (old format). Check for:
- a list of steps (with checkboxes) -- in the body or a Steps comment
- a design section -- in the body or a Design comment
- a diagram -- in the body or a Diagram comment
- links to relevant documentation, code, resources, and related issues
- a list of prerequisites, and if so, ask the user if those have been completed
- a link to one or more pull requests -- if so, read their diffs to understand what has already been implemented
Try to verify, from the comments and pull requests, which steps have been completed, and which are still pending.
If a durable-memory CLI is configured, query it with the issue's distinctive terms after reading. See the memory tool's own integration doc for mechanics.
Tell the user what you have learned from reading the issue, and ask any clarifying questions you may have about the work to be done.
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.

