Skills › AI & Agent Engineering › Skill & prompt authoring
update-skills
Create or update repository skills and instructions when major learnings are discovered during a session. Use when the user says "learn!", when a significant pattern or pitfall is identified, or when reusable domain knowledge should be captured for future sessions.
The full skill
—
name: update-skills
description: Create or update repository skills and instructions when major learnings are discovered during a session. Use when the user says "learn!", when a significant pattern or pitfall is identified, or when reusable domain knowledge should be captured for future sessions.
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<!– Customize this skill and select save to override its behavior. Delete that copy to restore the built-in behavior. –>
# Update Skills & Instructions
When a major repository learning is discovered — a recurring pattern, a non-obvious pitfall, a crucial architectural constraint, or domain knowledge that would save future sessions significant time — capture it as a skill or instruction so it persists across sessions.
## When to Use
– The user explicitly says **"learn!"** or asks to capture a learning
– You discover a significant pattern or constraint that cost meaningful debugging time
– You identify reusable domain knowledge that isn't documented anywhere in the repo
– A correction from the user reveals a general principle worth preserving
## Decision: Skill vs Instruction vs Learning
**Add a learning to an existing instruction** when:
– The insight is small (1-4 sentences) and fits naturally into an existing instruction file
– It refines or extends an existing guideline
– Follow the pattern in `.github/instructions/learnings.instructions.md`
**Create or update a skill** (`.github/skills/{name}/SKILL.md` or `.agents/skills/{name}/SKILL.md`) when:
– The knowledge is substantial (multi-step procedure, detailed guidelines, or rich examples)
– It covers a distinct domain area (e.g., "how to debug X", "patterns for Y")
– Future sessions should be able to invoke it by name
**Create or update an instruction** (`.github/instructions/{name}.instructions.md`) when:
– The rule should apply automatically based on file patterns (`applyTo`) or globally
– It's a coding convention, architectural constraint, or process rule
– It doesn't need to be invoked on demand
## Procedure
### 1. Identify the Learning
Reflect on what went wrong or what was discovered:
– What was the problem or unexpected behavior?
– Why was it a problem? (root cause, not symptoms)
– How was it fixed or what's the correct approach?
– Can it be generalized beyond this specific instance?
### 2. Check for Existing Files
Before creating new files, search for existing skills and instructions that might be the right home:
“`
# Check existing skills
ls .github/skills/ .agents/skills/ 2>/dev/null
# Check existing instructions
ls .github/instructions/ 2>/dev/null
# Search for related content
grep -r "related-keyword" .github/skills/ .github/instructions/ .agents/skills/
“`
### 3a. Add to Existing File
If an appropriate file exists, add the learning to its `## Learnings` section (create the section if it doesn't exist). Each learning should be 1-4 sentences.
### 3b. Create a New Skill
If the knowledge warrants a standalone skill:
1. Choose the location:
– `.github/skills/{name}/SKILL.md` for project-level skills (committed to repo)
– `.agents/skills/{name}/SKILL.md` for agent-specific skills
2. Create the directory and SKILL.md with frontmatter:
“`markdown
—
name: {skill-name}
description: {One-line description of when and why to use this skill.}
—
# {Skill Title}
{Body with guidelines, procedures, examples, and learnings.}
“`
3. The `name` field **must match** the parent folder name exactly.
4. Include concrete examples — skills with examples are far more useful than abstract rules.
### 3c. Create a New Instruction
If the knowledge should apply automatically:
“`markdown
—
description: {When these instructions should be loaded}
applyTo: '{glob pattern}' # optional — auto-load when matching files are attached
—
{Content of the instruction.}
“`
### 4. Quality Checks
Before saving:
– Is the learning **general enough** to help future sessions, not just this one?
– Is it **specific enough** to be actionable, not just a vague principle?
– Does it include a **concrete example** of right vs wrong?
– Does it avoid duplicating knowledge already captured elsewhere?
– Is the description clear enough that the agent will know **when** to invoke/apply it?
### 5. Inform the User
After creating or updating the file:
– Summarize what was captured and where
– Explain why this location was chosen
– Note if any existing content was updated vs new content created