Codebase Knowledge Graph Q&A
Egonex-AI/Understand-Anything
Answers questions about a codebase by searching a prebuilt knowledge graph of its files, functions, classes and dependencies, not by rereading every source file.
Assessment: read-only inspection, codebase overview, value analysis, health checks, ADR consultation, decision analysis, multi-perspective critique.
Install Assessment
$ npx skills add notque/vexjoy-agent --skill assessment -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install notque/vexjoy-agent assessment --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/notque/vexjoy-agent.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/analysis/assessment .claude/skills/assessment && 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 "assessment" agent skill from https://github.com/notque/vexjoy-agent/tree/main/skills/analysis/assessment into .claude/skills/assessment/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "assessment", 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/notque/vexjoy-agent/tree/main/skills/analysis/assessmentType 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 notque/vexjoy-agent --skill assessment -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install notque/vexjoy-agent assessment --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/notque/vexjoy-agent.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/analysis/assessment .agents/skills/assessment && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "assessment" agent skill from https://github.com/notque/vexjoy-agent/tree/main/skills/analysis/assessment into .agents/skills/assessment/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "assessment", 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 notque/vexjoy-agent --skill assessment -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install notque/vexjoy-agent assessment --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/notque/vexjoy-agent.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/analysis/assessment .cursor/skills/assessment && 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 "assessment" agent skill from https://github.com/notque/vexjoy-agent/tree/main/skills/analysis/assessment into .cursor/skills/assessment/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "assessment", 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/notque/vexjoy-agent.git --path skills/analysis/assessment--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 notque/vexjoy-agent --skill assessment -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install notque/vexjoy-agent assessment --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/notque/vexjoy-agent.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/analysis/assessment .gemini/skills/assessment && 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 "assessment" agent skill from https://github.com/notque/vexjoy-agent/tree/main/skills/analysis/assessment into .gemini/skills/assessment/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "assessment", 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 notque/vexjoy-agent assessmentInstalls 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 notque/vexjoy-agent --skill assessment -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/notque/vexjoy-agent.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/analysis/assessment .github/skills/assessment && 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 "assessment" agent skill from https://github.com/notque/vexjoy-agent/tree/main/skills/analysis/assessment into .github/skills/assessment/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "assessment", 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 notque/vexjoy-agent --skill assessment -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install notque/vexjoy-agent assessment --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/notque/vexjoy-agent.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/analysis/assessment .opencode/skills/assessment && 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 "assessment" agent skill from https://github.com/notque/vexjoy-agent/tree/main/skills/analysis/assessment into .opencode/skills/assessment/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "assessment", 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
assessment- GitHub stars
- 438
- Token cost
- ~3.5k tokens
- SKILL.md length
- 1,317 words
- Files
- 30 (incl. scripts, references)
- Skills in repo
- 61
- Repo updated
- First seen
- Licence
- MIT
At a glance
Assessment: read-only inspection, codebase overview, value analysis, health checks, ADR consultation, decision analysis, multi-perspective critique.
- Works in 12 steps: SCOPE → GATHER → REPORT → …
- Tasks that involve Architecture decision records
- SKILL.md covers Mode Selection, Read-Only Inspection, Codebase Overview and Repo Value Analysis, plus 3 more sections
- Calls git, sqlite3 and curl
What it does
Assessment is an agent skill from notque/vexjoy-agent. Assessment: read-only inspection, codebase overview, value analysis, health checks, ADR consultation, decision analysis, multi-perspective critique.
Its SKILL.md is about 3.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 34 other files, including scripts and reference files (for example `references/adr-consultation/agent-prompts.md`, `references/adr-consultation/consultation-patterns.md` and `references/adr-consultation/consultation-preferred-patterns.md`).
It sits in Development, covering Architecture decision records and Codebase onboarding. The repository describes itself as: VexJoy AI Agent with Jev Intelligent Routing - /do routes plain-English requests to the right specialist agent and gates the work with reviews, tests, and a learning loop. The licence is MIT.
When your agent uses it
- Tasks that involve Architecture decision records
- Tasks that involve Codebase onboarding
Example prompts
- “/assessment”
Requirements
- Docker
- Pre-approved tools (allowed-tools): Read, Write, Bash, Grep, Glob, Edit, Task, Skill, Agent
Workflow steps
12 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 5218674. 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:
ReadWriteBashGrepGlobEditTaskSkillAgent
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships 1 file in scripts/, which the agent can run.
Shell commands in SKILL.md call:
gitsqlite3curlapt
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md. Its commands use git and curl, which can reach the network depending on how they are called.
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
Assessment loads about 3.5k tokens when it runs, and up to ~50k if it reads all its reference files. Until then it costs about 40 tokens; SKILL.md has 1,317 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: notes
The automated check noted patterns worth knowing about, such as sudo or a known installer.
- NoteMentions a .env fileSKILL.md:102
sensitive files (`.env`, `*.pem`, `*.key`, credentials) silently. - NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
allowed-tools: Read, Write, Bash, Grep, Glob, Edit, Task, Skill, Agent
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); the scripts in this folder are not scanned.
SKILL.md
The full file from notque/vexjoy-agent at commit 5218674, republished under its MIT licence (© notque). 1,317 words, ~3,498 tokens.
Download SKILL.mdSave it as
.claude/skills/assessment/SKILL.md (or your agent's skills folder). This skill also uses 29 other files; get the full folder from GitHub.- name
- assessment
- description
- Assessment: read-only inspection, codebase overview, value analysis, health checks, ADR consultation, decision analysis, multi-perspective critique.
- allowed-tools
- Read, Write, Bash, Grep, Glob, Edit, Task, Skill, Agent
- user-invocable
- true
- routing.not_for
- code review with findings (use review), building or fixing (use workflow)
- routing.triggers
- inspect without changing, read-only, audit current state, onboard to codebase, codebase structure, give me an overview, summarize this repo, repo value…
- routing.category
- analysis
- routing.pairs_with
- review, workflow, security
Assessment Skill
Seven modes for read-only analysis and decision support. Match the request to a mode, then follow that mode's phases.
Mode Selection
| Request pattern | Mode |
|---|---|
| Inspect, browse, explore without changing | Read-Only Inspection |
| Onboard, overview, summarize repo, codebase structure | Codebase Overview |
| Repo value analysis, compare repos, what can we learn | Repo Value Analysis |
| Service status, health check, uptime, validate endpoints | Service Health Check |
| Consult on ADR, challenge design, architecture consultation | ADR Consultation |
| Help me decide, decision matrix, pros/cons, trade-offs | Decision Scoring |
| Critique ideas, devil's advocate, stress test, roast | Multi-Persona Critique |
Read-Only Inspection
Safe exploration without modifying files or system state.
Phase 1: SCOPE
Parse the request. Determine target scope (file, directory, service, system-wide). Clarify before proceeding if scope could match dozens of results.
Phase 2: GATHER
Use read-only tools only.
Allowed: ls, find, wc, du, df, file, stat, ps, top -bn1,
uptime, free, pgrep, git status/log/diff/show/branch,
sqlite3 "SELECT ...", curl -s (GET only), date, env.
Forbidden: mkdir, rm, mv, cp, touch, chmod, chown,
git add/commit/push, file writes, INSERT/UPDATE/DELETE/DROP,
npm/pip/apt install, kill, systemctl restart.
Phase 3: REPORT
Lead with the answer. Show supporting evidence. List files examined. All claims must cite evidence.
Codebase Overview
4-phase exploration producing an evidence-backed onboarding report. Read-only.
Read any .claude/CLAUDE.md or CLAUDE.md in the repo root first. Skip
sensitive files (.env, *.pem, *.key, credentials) silently.
Phase 1: DETECT
Examine root directory. Identify project type from config files (package.json,
go.mod, pyproject.toml, pom.xml, Cargo.toml). Document: language,
framework, build system, dependencies. Load references/codebase-overview/exploration-strategies.md
for language-specific discovery commands.
Gate: Project type identified. Tech stack documented.
Phase 2: EXPLORE
Discover entry points, core modules, data models, API surfaces, configuration,
tests. Limit 20 files per category. Map directory structure (exclude
node_modules/, venv/, vendor/, dist/, build/, __pycache__/).
Gate: Entry points, core modules, data layer, API surface, config, tests documented.
Phase 3: MAP
Identify design patterns with file evidence. Map 5-10 key abstractions. Trace a typical request through the full stack. Analyze last 10 commits. All paths absolute. All claims cite source files.
Gate: Patterns identified, abstractions mapped, data flow documented.
Phase 4: SUMMARIZE
Generate report using references/codebase-overview/report-template.md.
Include "Where to Add New Code" section. Run post-exploration secret scan.
For deep-dive mode ("full picture"), launch 4 parallel domain agents via Task.
See references/codebase-overview/examples-and-errors.md for dispatch template.
Scripts: scripts/cartographer.py (quick), scripts/cartographer_omni.py
(100-metric), scripts/cartographer_ultimate.py (focused performance).
Repo Value Analysis
6-phase pipeline analyzing external repositories for adoptable ideas.
Phase 1: CLONE
Parse input (GitHub URL, local path, org/repo). git clone --depth 1.
Categorize files into zones (skills, agents, hooks, docs, tests, config, code,
other). Cap zones at ~100 files.
Phase 2: DEEP-READ (parallel)
Dispatch 1 Agent per zone (up to 8). Each reads EVERY file and produces:
component inventory, key techniques, notable patterns, gaps. Output to
/tmp/[REPO]-zone-[zone].md.
Gate: 75%+ agents returned.
Phase 3: INVENTORY (parallel with Phase 2)
Dispatch 1 Agent to catalog vexjoy-agent repo: agents, skills, hooks, scripts
with counts. Output to /tmp/self-inventory.md.
Phase 4: SYNTHESIZE
Read all zone findings and inventory. Build comparison table. Rate gaps:
HIGH/MEDIUM/LOW. Save draft to research-[REPO]-comparison.md.
Phase 5: AUDIT (parallel)
For each HIGH/MEDIUM recommendation, dispatch 1 audit Agent to verify: ALREADY
EXISTS, PARTIAL, or MISSING. Skip with --quick.
Phase 6: REPORT
Adjust recommendations from audit. Write final report: executive summary,
comparison table, already-covered, recommendations, verdict, next steps. Clean
/tmp/ files. Load references/repo-value-analysis/phase7-implement-template.md
for implementation dispatch.
Service Health Check
Deterministic service monitoring: Discover-Check-Report. Never report healthy without verifying process status independently.
Phase 1: DISCOVER
Locate service definitions: services.json, docker-compose, systemd units, or
user input. Build manifest: process pattern, health file, port, stale threshold
per service.
Phase 2: CHECK
Per service: (1) pgrep -f "<pattern>" for process status, (2) parse health
file JSON for staleness/status/connections, (3) ss -tlnp "sport = :<port>"
for port.
| Condition | Status |
|---|---|
| Process not running | DOWN |
| Running + health file missing/stale | WARNING |
| Running + status=error | ERROR |
| Running + disconnected >30min | WARNING |
| Running + port not listening | ERROR |
| Running + healthy | HEALTHY |
Gate: All services evaluated with evidence.
Phase 3: REPORT
Output summary (X/N healthy), highlight services needing action, provide copy-pasteable remediation. Never auto-restart without explicit flag.
For endpoint validation, load references/service-health-check/endpoint-validator.md.
For CVE source auditing, load references/service-health-check/cve-source-check.md.
ADR Consultation
3-agent parallel architecture consultation producing PROCEED or BLOCKED.
Phase 1: DISCOVER
Locate ADR (user path, .adr-session.json, or ask). Validate via
adr-query.py. Read full ADR. Create adr/{adr-name}/ directory.
Gate: ADR read, path validated, consultation directory created.
Phase 2: DISPATCH (parallel)
Launch all 3 agents in ONE message. Load references/adr-consultation/agent-prompts.md
for prompt templates:
- Contrarian (reviewer-perspectives): challenge assumptions, simpler alternatives
- User advocate (reviewer-perspectives): user impact, cognitive load
- Meta-process (reviewer-perspectives): system health, coupling, SPOF
For complex decisions, add 2 more agents (see agent-prompts.md).
Gate: All agents returned and wrote to adr/{adr-name}/.
Phase 3: SYNTHESIZE
Read agent files from disk. Extract concerns to adr/{adr-name}/concerns.md.
Determine verdict: all PROCEED = strong consensus, any BLOCK = hard block,
mixed = significant concerns. Write adr/{adr-name}/synthesis.md. Issue
verdict per references/adr-consultation/consultation-patterns.md.
Show full SKILL.md (523 more words)Show less
Decision Scoring
Weighted scoring for 2-4 options. Runs inline (no fork).
Step 1: Frame
State decision in one sentence. List 2-4 options. Eliminate non-starters first.
Step 2: Criteria
Default weights (adjust per domain -- load references/decision-helper/decision-archetypes.md
for build-vs-buy, database, cloud, framework, API, or operational tooling):
| Criterion | Weight | Measures |
|---|---|---|
| Correctness | 5 | Solves the actual problem |
| Complexity | 3 | Added complexity (lower = better) |
| Maintainability | 3 | Ease of change/debug |
| Risk | 3 | Failure mode severity |
| Effort | 2 | Implementation time |
| Familiarity | 2 | Team comfort |
| Ecosystem | 1 | Library/community support |
Lock weights before scoring. Do not adjust after seeing results.
Step 3: Score
Rate each option 1-10 per criterion with one-sentence justification. Calculate
sum(score * weight) / sum(weights).
Step 4: Analyze
All scores <6.0: no good option -- explore alternatives. Top two within 0.5: close call -- identify deciding criteria. Top leads by >0.5: recommend winner. If matrix contradicts intuition, ask which criterion is missing.
Step 5: Persist
Append to active ADR session (.adr-session.json) or task plan.
Multi-Persona Critique
5-persona parallel critique with consensus synthesis.
Phase 1: UNDERSTAND
Extract or generate numbered proposals. Each: what it does, why it matters, how it differs from status quo (2-4 sentences). Research domain first if generating.
Phase 2: BRIEF
Load references/multi-persona-critique/personas.md. Build prompts for 5
personas, each receiving ALL proposals:
- The Logician: coherence, assumptions, falsifiability
- The Pragmatic Builder: build cost, maintenance, simpler alternatives
- The Systems Purist: accidental complexity, separation of concerns
- The End User Advocate: friction, delight, solved-problem test
- The Skeptical Philosopher: human agency, dependency risk
Each produces: STRONG/PROMISING/WEAK/REJECT per proposal, ranked list, cross-cutting observations.
Phase 3: DISPATCH (parallel)
Launch all 5 via Agent. Wait for ALL to complete.
Phase 4: SYNTHESIZE
Build consensus matrix (proposals x personas x ratings). Classify: CONSENSUS (4+ agree), CONTESTED (2-3 split), OUTLIER (1 vs 4). Score: STRONG=3, PROMISING=2, WEAK=1, REJECT=0. Sum per proposal (0-15).
Phase 5: PRESENT
Generate report using references/multi-persona-critique/synthesis-template.md:
consensus matrix, features to build, worth investigating, disagreements,
shelve, cross-cutting insights.
For roast-style code critique with HN personas and file:line validation, load
references/multi-persona-critique/roast.md.
Deep References
Load on demand when the corresponding phase needs detailed lookup data.
| Context | Reference | Content |
|---|---|---|
| Codebase overview: language commands | references/codebase-overview/exploration-strategies.md | Per-language discovery commands |
| Codebase overview: report format | references/codebase-overview/report-template.md | 12-section report template |
| Codebase overview: deep-dive dispatch | references/codebase-overview/examples-and-errors.md | Parallel agent template, worked examples |
| Codebase overview: statistical lenses | references/codebase-overview/statistical-three-lenses.md | Three-lens statistical analysis |
| Codebase overview: metrics catalog | references/codebase-overview/statistical-metrics-catalog.md | 100-metric catalog |
| Codebase overview: statistical phases | references/codebase-overview/statistical-phase-details.md | Phase banners and workflows |
| Codebase overview: statistical examples | references/codebase-overview/statistical-analysis-examples.md | Real-world statistical workflows |
| Value analysis: implementation | references/repo-value-analysis/phase7-implement-template.md | Agent dispatch template |
| Health check: endpoint validation | references/service-health-check/endpoint-validator.md | Full endpoint validation methodology |
| Health check: security headers | references/service-health-check/security-headers.md | HSTS, CSP reference |
| Health check: endpoint config | references/service-health-check/endpoint-config-preferred-patterns.md | Config patterns |
| Health check: auth endpoints | references/service-health-check/auth-endpoint-patterns.md | Auth endpoint patterns |
| Health check: CVE sources | references/service-health-check/cve-source-check.md | CVE source check methodology |
| ADR: agent prompts | references/adr-consultation/agent-prompts.md | 3-agent prompt templates |
| ADR: artifact patterns | references/adr-consultation/consultation-patterns.md | Verdict display, artifact templates |
| ADR: failure modes | references/adr-consultation/consultation-preferred-patterns.md | Dispatch and verdict fixes |
| ADR: error recovery | references/adr-consultation/error-handling.md | Error recovery by phase |
| Decision: archetypes | references/decision-helper/decision-archetypes.md | Archetype-specific criteria weights |
| Decision: failure modes | references/decision-helper/decision-preferred-patterns.md | Scoring discipline patterns |
| Critique: personas | references/multi-persona-critique/personas.md | 5 persona specifications |
| Critique: synthesis | references/multi-persona-critique/synthesis-template.md | Consensus matrix and report |
| Critique: examples | references/multi-persona-critique/examples-and-errors.md | Worked examples, failure modes |
| Critique: roast mode | references/multi-persona-critique/roast.md | HN persona evidence-based critique |
© notque, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 29 other files (scripts, references) in skills/analysis/assessment of notque/vexjoy-agent.
- SKILL.md
- references/adr-consultation/agent-prompts.md
- references/adr-consultation/consultation-patterns.md
- references/adr-consultation/consultation-preferred-patterns.md
- references/adr-consultation/error-handling.md
- references/codebase-overview/examples-and-errors.md
- references/codebase-overview/exploration-strategies.md
- references/codebase-overview/report-template.md
- references/codebase-overview/statistical-analysis-examples.md
- references/codebase-overview/statistical-metrics-catalog.md
- references/codebase-overview/statistical-phase-details.md
- references/codebase-overview/statistical-three-lenses.md
- references/decision-helper/decision-archetypes.md
- references/decision-helper/decision-preferred-patterns.md
- references/multi-persona-critique/examples-and-errors.md
- references/multi-persona-critique/personas.md
- … and 14 more
Open the folder on GitHubat commit 5218674
Compare with similar skills
Assessment 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 |
|---|---|---|---|---|---|---|
| Assessment this skillnotque/vexjoy-agent | 438 | — | ~3.5k | Automated safety check: Notes | MIT | |
| Codebase Knowledge Graph Q&AEgonex-AI/Understand-Anything | 86k | 1 repos | ~1.2k | Automated safety check: Pass | MIT | |
| PR Design DocOpenHands/OpenHands | 90k | — | ~2.4k | Automated safety check: Pass | MIT | |
| Understand ExplainEgonex-AI/Understand-Anything | 86k | 1 repos | ~1.3k | Automated safety check: Pass | MIT | |
| Repomix Codebase Exploreryamadashy/repomix | 29k | 1 repos | ~2.7k | Automated safety check: Pass | MIT | |
| Code Graph Mermaid Diagramstrailofbits/skills | 7.4k | 1 repos | ~1.7k | Automated safety check: Pass | CC-BY-SA-4.0 |
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Gives an in-depth explanation of one file, function or module by reading the project's knowledge graph and checking that the graph is still fresh.
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Questions about Assessment
What does Assessment do?
Assessment: read-only inspection, codebase overview, value analysis, health checks, ADR consultation, decision analysis, multi-perspective critique. Assessment is an agent skill from notque/vexjoy-agent. Assessment: read-only inspection, codebase overview, value analysis, health checks, ADR consultation, decision analysis, multi-perspective critique.
When should I use Assessment?
Assessment fits situations like: tasks that involve Architecture decision records; tasks that involve Codebase onboarding.
How do I install Assessment in Claude Code?
Run `npx skills add notque/vexjoy-agent --skill assessment -a claude-code`. Or copy the skill folder (skills/analysis/assessment in notque/vexjoy-agent) into .claude/skills/assessment in your project. Claude Code loads it when a task matches its description.
How do I install Assessment in Codex?
Run `npx skills add notque/vexjoy-agent --skill assessment -a codex`. Or copy the skill folder (skills/analysis/assessment in notque/vexjoy-agent) into .agents/skills/assessment in your project. Codex loads it when a task matches its description.
Can I use Assessment 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 notque/vexjoy-agent --skill assessment -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/assessment, .gemini/skills/assessment, .github/skills/assessment and .opencode/skills/assessment in your project.
What does Assessment need to run?
Going by SKILL.md and its folder, Assessment needs the command-line tools its instructions call (git, sqlite3, curl and apt). Our summary lists: Docker. Its frontmatter pre-approves these tools: Read, Write, Bash, Grep, Glob, Edit, Task, Skill, Agent.
Does Assessment access the network?
SKILL.md contains no URLs. Its commands use git and curl, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
Is Assessment safe to install?
Our automated static check of SKILL.md found notes only (mentions a .env file; pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does Assessment use?
Assessment 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 Assessment use?
About 3.5k tokens (SKILL.md is roughly 14k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 46k tokens, read only when the agent opens those files.
What are the alternatives to Assessment?
Skills that share tags, products or a category with Assessment: Codebase Knowledge Graph Q&A (Egonex-AI/Understand-Anything, 86k stars), PR Design Doc (OpenHands/OpenHands, 90k stars), Understand Explain (Egonex-AI/Understand-Anything, 86k stars) and Repomix Codebase Explorer (yamadashy/repomix, 29k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Assessment?
notque (a GitHub user) maintains it in notque/vexjoy-agent, which has 438 GitHub stars. The repository holds 61 skills in this directory. The repository was last updated on October 3, 2026.
Source: notque/vexjoy-agent on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.