Workspace Surface Audit
affaan-m/ECC
Audit the active repo, MCP servers, plugins, connectors, env surfaces, and harness setup, then recommend the highest-value ECC-native skills, hooks, agents, and operator workflows.
Structured pre-design questioning to surface hidden constraints before any architecture decision is locked in.
MITAuto-check passed
Install Discovery
$ npx skills add avelikiy/great_cto --skill discovery -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install avelikiy/great_cto discovery --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/avelikiy/great_cto.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/discovery .claude/skills/discovery && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "discovery" agent skill from https://github.com/avelikiy/great_cto/tree/main/skills/discovery into .claude/skills/discovery/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "discovery", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/avelikiy/great_cto/tree/main/skills/discoveryType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add avelikiy/great_cto --skill discovery -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install avelikiy/great_cto discovery --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/avelikiy/great_cto.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/discovery .agents/skills/discovery && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "discovery" agent skill from https://github.com/avelikiy/great_cto/tree/main/skills/discovery into .agents/skills/discovery/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "discovery", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add avelikiy/great_cto --skill discovery -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install avelikiy/great_cto discovery --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/avelikiy/great_cto.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/discovery .cursor/skills/discovery && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "discovery" agent skill from https://github.com/avelikiy/great_cto/tree/main/skills/discovery into .cursor/skills/discovery/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "discovery", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/avelikiy/great_cto.git --path skills/discovery--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add avelikiy/great_cto --skill discovery -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install avelikiy/great_cto discovery --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/avelikiy/great_cto.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/discovery .gemini/skills/discovery && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "discovery" agent skill from https://github.com/avelikiy/great_cto/tree/main/skills/discovery into .gemini/skills/discovery/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "discovery", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install avelikiy/great_cto discoveryInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add avelikiy/great_cto --skill discovery -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/avelikiy/great_cto.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/discovery .github/skills/discovery && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "discovery" agent skill from https://github.com/avelikiy/great_cto/tree/main/skills/discovery into .github/skills/discovery/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "discovery", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add avelikiy/great_cto --skill discovery -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install avelikiy/great_cto discovery --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/avelikiy/great_cto.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/discovery .opencode/skills/discovery && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "discovery" agent skill from https://github.com/avelikiy/great_cto/tree/main/skills/discovery into .opencode/skills/discovery/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "discovery", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
discovery- GitHub stars
- 102
- Token cost
- ~1k tokens
- SKILL.md length
- 434 words
- Files
- 1
- Skills in repo
- 27
- Repo updated
- First seen
- Licence
- MIT
At a glance
Structured pre-design questioning to surface hidden constraints before any architecture decision is locked in.
- Works in 7 steps: Who depends on this? → What's the scale today, what's it in 6… → What MUST not change? → …
- SKILL.md covers The 7 discovery dimensions, Output, When to skip and Common gotchas
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Discovery is an agent skill from avelikiy/great_cto. 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.
Its SKILL.md is about 1k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
The repository describes itself as: You already have the agent. This is everything around it. greatcto runs Claude Code as a pipeline of 70 specialist agents — an independent model checks each stage before the next… The licence is MIT.
Example prompts
- “/discovery”
Requirements
- Pre-approved tools (allowed-tools): Read, Grep, Glob, Bash(git:*), Bash(bd:*)
Workflow steps
7 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit 97dd037. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves these tools, so the agent can use them without asking each time:
ReadGrepGlobBash(git:*)Bash(bd:*)
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown).
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Discovery loads about 1k tokens when it runs. Until then it costs about 53 tokens; SKILL.md has 434 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from avelikiy/great_cto at commit 97dd037, republished under its MIT licence (© avelikiy). 434 words, ~1,025 tokens.
Download SKILL.mdSave it as
.claude/skills/discovery/SKILL.md (or your agent's skills folder).- 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.
- allowed-tools
- Read, Grep, Glob, Bash(git:*), Bash(bd:*)
- when_to_use
- Apply BEFORE producing architecture docs, audit findings, security plans: - architect, before writing ARCH-*.md - project-auditor, at the start of /audit…
- effort
- medium
- paths
- docs/**, .great_cto/**, README*
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?).
Show full SKILL.md (169 more words)Show less
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:
## 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.
© avelikiy, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in skills/discovery of avelikiy/great_cto.
Open the folder on GitHubat commit 97dd037
Compare with similar skills
Discovery next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Discovery this skillavelikiy/great_cto | 102 | — | ~1k | Automated safety check: Pass | MIT | |
| Workspace Surface Auditaffaan-m/ECC | 276k | 3 repos | ~1.3k | Automated safety check: Notes | MIT | |
| Wobbling Ty Constraint Orderastral-sh/ruff | 50k | — | ~838 | Automated safety check: Pass | MIT | |
| Constraint-Driven Developmentaddyosmani/agent-skills | 104k | 2 repos | ~5.2k | Automated safety check: Pass | MIT | |
| Aria Hidden Bodythedaviddias/Front-End-Checklist | 74k | — | ~444 | Automated safety check: Pass | MIT | |
| Aria Hidden Focusthedaviddias/Front-End-Checklist | 74k | — | ~468 | Automated safety check: Pass | MIT |
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Questions about Discovery
What does Discovery do?
Structured pre-design questioning to surface hidden constraints before any architecture decision is locked in. Discovery is an agent skill from avelikiy/great_cto. Structured pre-design questioning to surface hidden constraints before any architecture decision is locked in.
How do I install Discovery in Claude Code?
Run `npx skills add avelikiy/great_cto --skill discovery -a claude-code`. Or copy the skill folder (skills/discovery in avelikiy/great_cto) into .claude/skills/discovery in your project. Claude Code loads it when a task matches its description.
How do I install Discovery in Codex?
Run `npx skills add avelikiy/great_cto --skill discovery -a codex`. Or copy the skill folder (skills/discovery in avelikiy/great_cto) into .agents/skills/discovery in your project. Codex loads it when a task matches its description.
Can I use Discovery in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add avelikiy/great_cto --skill discovery -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/discovery, .gemini/skills/discovery, .github/skills/discovery and .opencode/skills/discovery in your project.
What does Discovery need to run?
SKILL.md names no scripts, command-line tools or credentials: Discovery is instructions for the agent only. Its frontmatter pre-approves these tools: Read, Grep, Glob, Bash(git:*), Bash(bd:*).
Does Discovery access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Discovery safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Discovery use?
Discovery is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Discovery use?
About 1k tokens (SKILL.md is roughly 4.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Discovery?
Skills that share tags, products or a category with Discovery: Workspace Surface Audit (affaan-m/ECC, 276k stars), Wobbling Ty Constraint Order (astral-sh/ruff, 50k stars), Constraint-Driven Development (addyosmani/agent-skills, 104k stars) and Aria Hidden Body (thedaviddias/Front-End-Checklist, 74k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Discovery?
avelikiy (a GitHub user) maintains it in avelikiy/great_cto, which has 102 GitHub stars. The repository holds 27 skills in this directory. The repository was last updated on October 9, 2026.
Source: avelikiy/great_cto on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.