spec-grooming
Audit ticket completeness and validate system consistency before dev starts.
Skill by ervis
Chalk Labs
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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/ervis-spec-grooming
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: security
Reviews
Write a reviewNo reviews yet. Installed it? Reviews come from verified installers only. How reviews work
Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/spec-grooming
What's inside
- Skill name
spec-grooming- Description
- Audit ticket completeness and validate system consistency before dev starts.
- License
- NOASSERTION
- Instructions
- 186 lines in SKILL.md · view on GitHub
Files (1)
- SKILL.md
The license isn't open source, so the instructions aren't shown here. Read SKILL.md on GitHub
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design-doc
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Write a design doc for agent implementation.
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Write all responses in ASD-STE100 Simplified Technical English.
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doc-reduce
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Reduce a document to its concise form: every word carries meaning, like a math book where nothing can be removed without losing information.
SkillCFreshness: CClaude Code +9 - 0.467score
laconic
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Default communication mode.
SkillCFreshness: CClaude Code +9 - 0.464score
rails-code-review
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Review Ruby code for clean code principles and improve readability and maintainability
SkillCFreshness: CClaude Code +9 - 0.463score
qrspi-explore
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Iterative research exploration — one question per round, research it, Socratically probe the answer, refine until complete or capped
SkillCFreshness: CClaude Code +9 - 0.460score
qrspi-pr
ervis
Create a pull request with context from the design discussion
SkillCFreshness: CClaude Code +9 - 0.460score
qrspi-design
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Design discussion — align on where we are going before planning how
SkillCFreshness: CClaude Code +9 - 0.460score
qrspi-implement
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Execute the plan phase by phase with verification checkpoints
SkillCFreshness: CClaude Code +9 - 0.460score
qrspi-research
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Objective codebase research driven by questions — facts only, no opinions
SkillCFreshness: CClaude Code +9 - 0.457score
qrspi-structure
ervis
Structure outline — vertical slices with test checkpoints
SkillCFreshness: CClaude Code +9 - 0.457score
qrspi-plan
ervis
Tactical implementation plan — the agent's working document
SkillCFreshness: CClaude Code +9
Signals
- Stars
- 0
- Forks
- 0
- Open issues
- 0
- Last commit (this folder)
- Jul 16, 2026 (3 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- NOASSERTION
- Repository
- github.com/ervis/skilladiko
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
More from ervis
- 0.515score
design-doc
ervis
Write a design doc for agent implementation.
SkillBFreshness: BClaude Code +9 - 0.511score
simple-language
ervis
Write all responses in ASD-STE100 Simplified Technical English.
SkillBFreshness: BClaude Code +9 - 0.469score
doc-reduce
ervis
Reduce a document to its concise form: every word carries meaning, like a math book where nothing can be removed without losing information.
SkillCFreshness: CClaude Code +9 - 0.467score
laconic
ervis
Default communication mode.
SkillCFreshness: CClaude Code +9 - 0.464score
rails-code-review
ervis
Review Ruby code for clean code principles and improve readability and maintainability
SkillCFreshness: CClaude Code +9 - 0.463score
qrspi-explore
ervis
Iterative research exploration — one question per round, research it, Socratically probe the answer, refine until complete or capped
SkillCFreshness: CClaude Code +9
Done for you
Rather not set it up yourself?
Chalk Labs scopes, builds and runs agents for your team: the task audit, the eval harness, the integrations and the weekly ops report. Fixed scope, priced before we start.
See how we build AI agents →Read the case studies
Chalk Labs is a two-founder AI and growth studio. We build AI agents, CRMs and MVPs for Web3 and AI companies, and have shipped 50+ product and token launches.
- launches shipped
- 50+
- launches shipped
- media placements
- 500+
- media placements
- founders on every account
- 2
- founders on every account
Press we've placed: Forbes · CoinDesk · Decrypt · Cointelegraph · The Block
Rahil Jain, Co-founder, Chalk Labs. Ex-Goldman Sachs engineer. You talk to the person who builds it.
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Cite this page
spec-grooming skill. Agent Mart. https://agentmart.dev/skills/ervis-spec-grooming (last updated 2026-10-24)