discovery
Structured pre-design questioning to surface hidden constraints before any architecture decision is locked in.
Skill by avelikiy
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/avelikiy-discovery
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: design
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/discovery
Tools it pre-approves 5
From allowed-tools in SKILL.md: the agent may use these without asking you each time.
Read,Grep,Glob,Bash(git:*),Bash(bd:*)
What's inside
- Skill name
discovery- Description
- Structured pre-design questioning to surface hidden constraints before any architecture decision is locked in. Forces the architect/auditor/reviewer to enumerate what they DON'T know before proposing.
- License
- MIT
- Allowed tools
- Read,, Grep,, Glob,, Bash(git:*),, Bash(bd:*)
- Instructions
- 101 lines in SKILL.md · view on GitHub
Before installing
- Pre-approves some shell commands
Files (1)
- SKILL.md
SKILL.md (first lines)
# Discovery — surface hidden constraints first The biggest cause of bad agent output is missing context. Before locking in a decision, enumerate what you don't know and surface it. ## The 7 discovery dimensions For any non-trivial request, walk through these and record findings in the report's "Context" section: ### 1. Who depends on this? - What other services / teams consume the thing you're changing? - Are there public consumers (open API, OSS users)? - Is there a deprecation path if you break compatibility? Grep for: `grep -rE "import.*<your-module>|require.*<your-module>"` in the repo and any sibling repos you have access to. ### 2. What's the scale today, what's it in 6 months? - Current traffic: requests/sec, queries/sec, MB/day, daily-active-users - Storage: rows in main tables, size on disk - Cost: monthly LLM spend, infra spend - 6-month projection: linear? exponential? unknown? If unknown, write: "scale unknown — request from user before proceeding." ### 3. What MUST not change? - Existing API contracts (backward compatibility window) - Database schema columns referenced by reporting / BI - File formats consumed by other tools - Regulatory commitments (audit log retention, SLA RPO/RTO) ### 4. What's the budget? - Monthly cost ceiling (LLM + infra) - Headcount: 1-person task vs cross-team effort - Calendar: "must ship by X" vs "best by Y" If unstated, default to "small project_size, 1-engineer-week, <$200/mo budget." Surface this default in the report so the user can correct. ### 5. What's the failure mode that matters? Ask: "If this feature breaks at 3am, what gets paged?" - Data loss → CRITICAL - Wrong answer to user → HIGH - Slow response → MEDIUM - Bad UX (cosmetic) → LOW The failure mode dictates investment level (e.g., do you need a canary? A circuit breaker? Just a feature flag?). ### 6. What's already been tried? - Search Beads: `bd search "<keyword>"` — has this been attempted before? - Search docs/decisions: any superseded ADR on this topic? - Search lessons.md: any past learning about this pattern? If past work exists, build on it. Don't redo it. ### 7. Who decides? - Is there a CTO sign-off needed (gate:plan, gate:ship)? - Is there a compliance reviewer required (PCI for fintech, HIPAA for healthcare)? - Does this need an RFC (multi-team decision)? ## Output A discovery section at the top of your report: ```markdown ## Context - **Consumers:** <list, or "unknown — TBD with user"> - **Scale:** <today, 6mo projection> - **Frozen contracts:** <list, or "none identified"> - **Budget:** <cost + time + people> - **Failure-mode tier:** Critical | High | Medium | Low - **Prior work:** <links to ADRs/lessons, or "none found"> - **Decision-makers:** <gate or RFC required> ``` ## When to skip - **nano project_size** — discovery is overhead. Skip and document that you skipped: "nano — discovery skipped per skill rules." - **Pure utility extraction** with no behaviour change — skip. - **Verbal bug-fix from user** with clear repro — skip. ## Common gotchas - **Don't assume.** If you write "I assume the user wants X", that assumption belongs in Context as a question, not as a fact. - **Don't outsource to user.** Discovery is YOUR job. Bring back as many answers as Glob/Grep/git can produce. Only ask the user for what code cannot tell you.
From avelikiy/great_cto, MIT.
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Signals
- Stars
- 105
- Forks
- 13
- Open issues
- 5
- Last commit (this folder)
- May 28, 2026 (5 months ago)
- Last release
- Oct 23, 2026 (7 days ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/avelikiy/great_cto
- Website
- greatcto.systems
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
More from avelikiy
- 0.776score
deploy-landed
avelikiy
Prove a deploy landed — the served revision is the commit you meant, its env is present, and the product does its job — instead of trusting the deploy…
SkillAFreshness: A★ 105Claude Code +9 - 0.776score
lifecycle-messaging
avelikiy
Email/SMS lifecycle and deliverability framework for SMB Product-Builder products that send transactional or lifecycle messages (booking reminders, CRM…
SkillAFreshness: A★ 105Claude Code - 0.776score
aesthetic-instrument
avelikiy
great_cto's own committed aesthetic — the instrument panel.
SkillAFreshness: A★ 105Claude Code +9 - 0.776score
brainstorming
avelikiy
Structured idea generation + multi-LLM debate for the product-owner stage.
SkillAFreshness: A★ 105Claude Code - 0.776score
committed-aesthetic
avelikiy
How to write — and how to use — a skill that IS one aesthetic rather than a catalogue of them.
SkillAFreshness: A★ 105Claude Code +9 - 0.776score
migration-ready-schema
avelikiy
Data-model rules that make a schema importable from day one, so the migration-import-engineer is never blocked on missing columns.
SkillAFreshness: A★ 105Claude Code +9
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Cite this page
discovery skill. Agent Mart. https://agentmart.dev/skills/avelikiy-discovery (last updated 2026-10-24)