writing-skills
Use when creating new skills, editing existing skills, or verifying skills work before deployment
Skill by GanyuanRan
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/ganyuanran-writing-skills
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
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About
Use cases: writing
Reviews
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What's inside
- Skill name
writing-skills- Description
- Use when creating new skills, editing existing skills, or verifying skills work before deployment
- License
- MIT
- Instructions
- 117 lines in SKILL.md · view on GitHub
Files (2)
- SKILL.md
- testing-skills-with-subagents.md
SKILL.md (first lines)
# Writing Skills ## Purpose Create the smallest reusable skill that changes decisions or improves task execution without constraining unrelated work. Skill changes use behavior validation, not a code TDD route. This validation does not require loading `aegis:test-driven-development`. ## Default Path ### 1. Establish Need And Ownership - Name the reusable behavior gap, intended users/hosts, and non-goals. - Check whether an existing skill, project rule, host adapter, or automated check already owns it. Prefer the smallest existing owner. - For an existing skill, inspect its references, manifests or generated copies, discovery tests, and bundled resources before changing or retiring them. - Create a skill only for reusable, non-obvious guidance. Keep one-off project conventions in the project owner and automate mechanical constraints when practical. ### 2. Record Behavior Before Editing Use representative tasks, not questions that merely ask the agent to recite instructions. - New skill: run a no-skill control. - For an existing skill, run the current version first; add a no-skill ablation only when testing whether the skill itself needs to exist. - Cover positive triggers, negative near-misses, and a pressure or application case appropriate to the skill type. - Record decisions, missed or extra invocations, unsafe workarounds, evidence references, and unknowns. Do not treat line or byte counts as behavior proof. If meaningful behavior cannot be evaluated, stop at `needs-verification`; do not claim that the skill is deployment-ready or capability-preserving. ### 3. Design The Minimum Instruction Surface - Assume the agent is capable. Include only non-obvious context, decision criteria, safety boundaries, and steps whose omission caused an observed gap. - Match specificity to risk: allow judgment for open work; use exact sequences only for fragile, permission-sensitive, or safety-critical operations. - Keep the description concise, third-person, and discriminating. State the capability and when it applies; add an exclusion only when it prevents likely misrouting. Do not turn the description into a procedural shortcut. - Keep the executable default path and non-omittable constraints in `SKILL.md`. Move substantial conditional detail to a direct reference and state the evidence trigger for reading it. - Keep references one level deep where practical. Do not load every reference by default or duplicate its content in the main body. - Add an example only when it materially stabilizes a decision or output. One representative example is normally enough. - Keep portable method instructions host-neutral. Put host tool names, install paths, and UI choreography in their host-owned documentation. The canonical repository shape is `skills/<skill-name>/SKILL.md` with only the supporting references, scripts, or assets the workflow actually uses. Use the repository's host docs or the target host's live specification for optional metadata instead of copying a vendor manual into the skill. ### 4. Make The Smallest Change Address observed gaps and remove superseded duplication in the same slice. Preserve public attribution and any externally supported contract. When retiring an internal owner, fallback, or resource, compose `aegis:anti-entropy-governance`; do not leave a compatibility copy without dependency evidence. Do not convert one model's phrasing, one historical incident, or a hypothetical edge case into a universal rule. ### 5. Validate The Candidate Re-run the same positive, negative, and pressure/application scenarios under a comparable model, tool, and host configuration. Compare outcomes, not wording. Also verify: - frontmatter, name, and description parse on supported hosts; - intended requests still discover the skill and near-misses do not; - every conditional reference is reachable from an explicit trigger; - changed scripts run successfully; - retired files and instructions have no live references; - repository workflow, boundary, packaging, and host checks relevant to the touched surface pass. If behavior regresses, restore the missing obligation or narrow the change; do not add a second owner or fallback to mask it. ## Scenario Selection | Skill type | Representative evidence | | --- | --- | | Discipline or safety | realistic pressure and authorization boundaries | | Technique | application, variation, and missing-information cases | | Pattern | recognition, application, and counter-example cases | | Reference | retrieval, correct use, and common-gap cases | For a complex or high-risk skill where an independent evaluator adds confidence, read `testing-skills-with-subagents.md`. ## Completion Record Keep the result compact and auditable in natural prose or equivalent fields: - behavior gap and canonical owner; - baseline and candidate scenario results; - retained and retired obligations/resources; - trigger and reference checks; - verification commands and uncovered hosts/models; - status: `verified`, `needs-verification`, or `blocked`. This is method-pack evidence, not authoritative completion or deployment approval.
From GanyuanRan/Aegis, MIT.
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Signals
- Stars
- 1,383
- Forks
- 78
- Open issues
- 1
- Last commit (this folder)
- Sep 20, 2026 (1 month ago)
- Last release
- Oct 21, 2026 (7 days ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/GanyuanRan/Aegis
- Website
- autoloom.codes/aegis/
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Cite this page
writing-skills. Agent Mart. https://agentmart.dev/skills/ganyuanran-writing-skills (last updated 2026-10-24)