ai-assist-project-summary
Generate a plain-language project overview, comprehensive engineer status update, and surgical documentation enhancement. Reads project docs, specs, dependencies, and git history. Use when onboarding, returning from time off, refreshing stale docs, or preparing project overviews.
Supply asset profile
Research and knowledge work
Deep research, source comparison, literature review, RAG, knowledge search, and reports.
Scenario
Research agents
I need my agent to research a topic, compare sources, and produce a concise report.
Agent fit
Claude Code + CLI + Codex
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add jparkerweb/ai-assist-skills --skill ai-assist-project-summary
Maintenance
fresh
3d since push
Risk
Needs review
License is unclear
GitHub quality
88
61/100 Quality · 70/100 Trust
Coverage tags
Review notes
License is unclear · Financial research output is not financial advice; require human review before any live investment decision
Agent adoption scorecard
Trust, audit, and install readiness at a glance
These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.
Quality
PromisingUseful candidate, but compare it with alternatives before adopting.
Trust
Sandbox onlyUseful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
Audit
Needs reviewA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Human review before install
Run only in a sandbox and compare close alternatives before using it for real work.
Stars
88 GitHub stars
Repo activity
88 stars, 12 forks
Maintenance
3d since push
License
Unknown
Install
npx skills add jparkerweb/ai-assist-skills --skill ai-assist-project-summary
Install safety
standard package or runtime install path
Permission surface
shell or command execution, filesystem or document access
Agent outcomes
No agent outcome data yet
Docs
Strong README/SKILL.md context
Risk summary
Review before production
- Repository license is unknown; could be ambiguous for reuse or redistribution.
- Financial research output is not financial advice; require human review before any live investment decision.
- License is unclear
- Quality score needs review
Install readiness
Install path available
- Install path is available
- Repository evidence is available
- License is unclear
- No Agent Proven outcome evidence yet
Agent-readable metadata
Machine-readable decision data for this skill.
Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.
Suited tasks
- Research agents workflows
- Claude Code teams
- builders willing to evaluate younger projects
- Search sources
Suited agents
Install decision
- Command
- npx skills add jparkerweb/ai-assist-skills --skill ai-assist-project-summary
- Policy
- review
- Human review
- yes
Trust and risk
- Trust
- 62/100
- Audit
- 74/100
- Risk level
- Needs review
Outcome loop
- Endpoint
- /api/agent/outcome
- Event ID
- resolve
- Outcomes
- 5
Install command
npx skills add jparkerweb/ai-assist-skills --skill ai-assist-project-summaryDo not use when
- teams that need a vendor-supported SLA
- production agents without a repository review
- Repository license is unknown; could be ambiguous for reuse or redistribution.
- High-risk permission hints: Shell or command execution
- License is unclear
Alternative
Last30days Skill
53.5K Stars
npx skills add mvanhorn/last30days-skill -g
Alternative
Academic Research Skills
38.4K Stars
npx skills add Imbad0202/academic-research-skills
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28.0K Stars
npx skills add assafelovic/gpt-researcher
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DeepResearch
19.8K Stars
npx skills add Alibaba-NLP/DeepResearch
Agent safety v2
46/100 · Avoid automatic install
Sparse or mixed signals. Useful for discovery, but not for autonomous installation.
Test manually in an isolated workspace and compare against safer alternatives.
high
Shell or command execution
Skill metadata references terminal, CLI, shell, subprocess, or command execution workflows.
medium
Network access
Skill likely fetches remote pages, APIs, repositories, or external services.
medium
Filesystem access
Skill may read or write project files, documents, generated artifacts, or local workspace state.
- High-risk permission hints: Shell or command execution
- License is unclear
Install targets
Install this skill in your agent workflow
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
OpenAgentSkill CLI
Resolve policy, run the source installer safely, and report a verified install receipt.
$ npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.2.1/openagentskill-0.2.1.tgz install jparkerweb-ai-assist-project-summaryAgent resolve plan
Let an agent verify fit before installing.
The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.
Open JSON
/api/agent/resolve?task=Use%20ai-assist-project-summary%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20ai-assist-project-summary%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/jparkerweb-ai-assist-project-summary/install
Agent should check
- Task fit and alternatives from Resolve API.
- Audit score, trust score, and safety policy warnings.
- Install target compatibility for Codex, Claude Code, Cursor, or CLI.
Copy prompt
Task: Use ai-assist-project-summary in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20ai-assist-project-summary%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/jparkerweb-ai-assist-project-summary/install
Install command: npx skills add jparkerweb/ai-assist-skills --skill ai-assist-project-summary
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent handoff
Give an agent the install path, not another directory page.
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
Install handoff
/api/skills/jparkerweb-ai-assist-project-summary/install
LLM text format
/api/skills/jparkerweb-ai-assist-project-summary/install?format=text
Find alternatives
/api/skills/search?q=ai-assist-project-summary&limit=3
Agent prompt
Use ai-assist-project-summary for this task. Review https://www.openagentskill.com/api/skills/jparkerweb-ai-assist-project-summary/install, then install with: npx skills add jparkerweb/ai-assist-skills --skill ai-assist-project-summaryRegistry metadata
Agent-readable profile for automatic skill selection.
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
Manifest
/api/registry/manifest/jparkerweb-ai-assist-project-summary
LLM text
/api/registry/manifest/jparkerweb-ai-assist-project-summary?format=text
Install alias
/api/registry/install/jparkerweb-ai-assist-project-summary
Recommend
/api/registry/recommend?task=Use%20ai-assist-project-summary%20in%20an%20agent%20workflow&limit=3
Agent fit
Research agents
Use-case tags
Platforms
Claude Code
Audit report
Needs review · 74/100
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Fallback candidate for Research agents
Prototype with this skill first; keep a fallback candidate ready.
Role in stack
Fallback candidate
Primary fit
Research agents
Trust label
Prototype first
Install path
Command ready
Use when
- Research agents workflows
- Claude Code teams
- builders willing to evaluate younger projects
Evidence
- recent repository activity
- install command or GitHub repo available
- 61/100 quality profile
- 2 OpenAgentSkill engagement events
review first
- Repository license is unknown; could be ambiguous for reuse or redistribution.
Implementation path
- 1Install it in a sandbox agent and run one Research agents task end to end.
- 2Compare output quality, latency, and failure behavior against at least one alternative.
- 3Promote it into production only after reviewing repository permissions, license, and maintenance signals.
Trust profile
Sandbox only
Useful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
GitHub adoption
CHECK88 GitHub stars
Stars/forks activity
CHECK88 stars, 12 forks; issue activity unavailable in current metadata
Recent maintenance
PASS3d since push
License clarity
CHECKUnknown
Good signals
- AI review approved
- Install path is available
- Repository evidence is available
- Recently maintained repository
- Install command has no obvious high-risk pattern
- Outcome loop is ready but needs first real agent run
Review before install
- Repository license is unknown; could be ambiguous for reuse or redistribution.
- Financial research output is not financial advice; require human review before any live investment decision.
- License is unclear
- Quality score needs review
- GitHub adoption: 88 GitHub stars
- Stars/forks activity: 88 stars, 12 forks; issue activity unavailable in current metadata
- License clarity: Unknown
- No real agent outcome reports yet
- Human review required before unattended installation
Recommended action
Run only in a sandbox and compare close alternatives before using it for real work.
Quality profile
Promising candidate for agent workflows
Useful candidate, but compare it with alternatives before adopting.
Workflow fit
Use this skill in these scenarios
Investigate faster
Research agents
I need my agent to research a topic, compare sources, and produce a concise report.
Manage repositories
GitHub automation
I need my agent to triage GitHub issues, review pull requests, and summarize repository changes.
Search private knowledge
RAG and knowledge
I need my agent to build a RAG workflow over documents and retrieve reliable context.
Workflow fit
Add it to a complete workflow
Find, compare, and synthesize
Research report agent
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Ingest, retrieve, and cite
RAG knowledge base
A workflow for document-heavy agents that ingest files, create searchable knowledge, retrieve relevant context, and answer with grounded sources.
Operate and verify web apps
Browser QA agent
A workflow for agents that navigate products, fill forms, take screenshots, and verify real user flows across web applications.
Alternative shortlist
Compare before you install
Similar skills that may fit this task.
Last30days Skill
Research the last 30 days across Reddit, X, YouTube, Hacker News, Polymarket, GitHub, and the web, then synthesize a grounded brief for an AI agent.
Academic Research Skills
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GPT Researcher
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DeepResearch
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Overview
--- name: ai-assist-project-summary description: "Generate a plain-language project overview, comprehensive engineer status update, and surgical documentation enhancement. Reads project docs, specs, dependencies, and git history. Use when onboarding, returning from time off, refreshing stale docs, or preparing project overviews." argument-hint: "[path or project name]" ---
# PROJECT SUMMARY
**Objective:** Generate a clear project overview and comprehensive engineer status update, then offer to enhance existing documentation. **When to use:** Onboarding, returning from time off, refreshing stale docs, preparing project overviews for stakeholders.
Start all responses with '📋 [Summary Step X: Name]'
## Role
Technical writer and project analyst who translates complex codebases into clear summaries and actionable status updates. Writes for engineers, product managers, and stakeholders alike.
## Context
**AGENTS.md check:** If `./AGENTS.md` exists, read it — follow project conventions, architecture, and patterns. If missing, warn: "No AGENTS.md found — proceeding without project context."
**Spec awareness:** If `specs/` exists, check for active work that affects project status.
**Read everything before writing:** 1. `./AGENTS.md` and `.agents-docs/` — project conventions, architecture, tech stack 2. `README.md` — current documentation state 3. `specs/*/overview.md` — active specs (excluding `specs/archive/`) 4. `docs/` — existing documentation 5. `package.json` / `*.csproj` / `Cargo.toml` / `go.mod` / `pyproject.toml` — dependencies and scripts 6. `git log --oneline -30` — recent activity 7. `git status` — current state
## Rules
1. **Layman's terms** — no jargon without inline definition. If expertise is required, rewrite. 2. **Evidence-based** — every claim from reading actual files. Never fabricate. 3. **Read before write** — never modify docs without reading them first. 4. **Enhance, never replace** — add to existing docs, never rewrite from scratch. 5. **Doc tier discipline** — permanent info in README, agent-facing info in AGENTS files, transient info in specs only. 6. **Chat-only output** — present all findings in chat. Never create or modify files without explicit user permission. 7. **Hierarchical structure** — big picture first, then drill down. 8. **Brief and concise** — tables over paragraphs, one line per concept. 9. **Part 2 is the primary deliverable** — prioritize depth and thoroughness in the engineer status update over Part 1 (project overview).
## Process
### Step 1: Gather Context & Generate Part 1
Read all context files listed above.
Read `references/part1-project-overview.md` for the project overview structure, project type detection table, and writing guidelines.
Detect the project type, adapt sections accordingly. Present Part 1 in chat: what it is, what it does, tech stack, key concepts, project structure, getting started, deployment environments (if applicable), compliance & security (if detected).
### Step 2: Engineer Status Update (Part 2)
Read `references/part2-engineer-status.md` for data sources, scanning instructions, and status categories.
Scan all data sources: - `git log` for recent commits and activity - `git branch -r` for active branches - `specs/` for planned and in-progress work - Code comments (TODO, FIXME, HACK, XXX, OPTIMIZE, REVIEW) via agent search tools - Test runner output if command is discoverable and safe to run
Present Part 2 in chat with all 5 status categories: Recently Completed, In Progress, Issues & Gaps, Upcoming & Roadmap, Suggested Improvements.
### Step 3: Documentation Enhancement (Part 3)
Read `references/doc-integration.md` for the documentation tier model, enhancement rules, and per-target guidance.
Read `references/output-template.md` for the output format and self-verification checklist.
Classify all findings by doc tier (permanent, agent-facing, transient). Present enhancement suggestions grouped by target document. Ask: "Enhance documentation with these findings? (All / Select targets / Skip)"
If user approves: read each target file, surgically integrate enhancements, present changes for review before writing.
### Self-Verification Checklist
> Canonical version in `references/output-template.md`. Brief version here for quick reference.
Before presenting, verify: - [ ] Every claim verified from actual files — no fabrication - [ ] A product manager could understand Part 1 without follow-up questions - [ ] A returning engineer could prioritize work from Part 2 without asking teammates - [ ] All technical terms defined inline - [ ] Current Status reflects actual git state and active specs - [ ] Compliance & Security section included if regulatory context detected - [ ] Documentation enhancements classified by correct doc tier - [ ] No transient info suggested for permanent docs
### Session End
``` 📋 [Summary Complete]
**What was done:** Project summary generated for [project name]. - Part 1: Project overview ([X] sections) - Part 2: Engineer status ([X] completed, [Y] in-progress, [Z] issues, [W] upcoming) - Part 3: [Documentation enhanced / Documentation unchanged] ```
**Next steps (ask user — do not auto-execute):** - Save summary to `specs/project-summary-<date>.md`? - Related: `/ai-assist-discovery` for deep research, `/ai-assist-tech-debt` for codebase health
## Recovery
| Issue | Solution | |-------|----------| | No AGENTS.md | Warn and proceed — gather context from README, package manifests, git history | | No README.md | Generate summary in chat; offer to create README from scratch | | Monorepo | Summarize root project; list packages as table with one-line descriptions | | Empty/new project | Note minimal state; focus on setup instructions and planned architecture | | No git history | Skip Part 2 status sections that require git data; note limitation | | No specs/ directory | Skip spec-related status items; note limitation |
## Important Reminders
**Response format:** Every response starts with `📋 [Summary Step X: Name]`
**Hard rules:** - Layman's terms — if expertise is required to understand the summary, rewrite it - Read before write — never update docs without reading them first - Evidence-based — only document what is verified in the codebase - Enhance, never replace — no "Replace" or full rewrite option for existing docs
**Process rules:** - Detect project type and adapt section structure - Doc tier discipline — permanent, agent-facing, and transient info go to different targets - Chat-only output — always ask before creating or modifying files
**Related:** `/ai-assist-discovery` for deep research, `/ai-assist-tech-debt` for codebase health assessment, `/ai-assist-security-audit` for security posture.
Technical details
- Version
- 1.0.0
- License
- Unknown
- Last updated
- Aug 21, 2026
- Published
- Aug 21, 2026
Decision snapshot
Fallback candidate
recent repository activity
Audit
Install review
Install and adoption review
- Security
- 73/100
- Maintenance
- 100/100
- Install
- 92/100
Agent-proven evidence
Agent-proven evidence
Outcome reports after resolve, review, install, and one narrow run.
- Success rate
- —
- Recent failure
- —
- Outcomes
- 0
- Output quality
- —
- Failed
- 0
- Not relevant
- 0
- Installs
- 0
- Risk blocked
- 0
- Setup needed
- 0
- Production
- 0
No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.
Install
Add to agent workflow
Free and open source. Review the report before installing into production agents.
Growth loop
Share kit
Scenario-led draft for ai-assist-project-summary, ready for a manual X post.
ai-assist-project-summary: Generate a plain-language project overview, comprehensive engineer status update, and surgica... 88 stars https://www.openagentskill.com/skills/jparkerweb-ai-assist-project-summary?ref=x
Optional reply with install command
Listing + install path for ai-assist-project-summary: https://www.openagentskill.com/skills/jparkerweb-ai-assist-project-summary?ref=x Install: npx skills add jparkerweb/ai-assist-skills --skill ai-assist-project-summary
Listing source
Registry indexed
This listing was indexed from public sources and is not marked official until a maintainer claim is approved.
- Creator
- jparkerweb
- Indexed by
- OpenAgentSkill community index
Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals.
Claim this skillOwner claim
Claim this skill listing
This Registry indexed listing is attributed to jparkerweb but is not marked official yet. Claim it to add a verified owner signal and make future launch, install, and audit updates easier to trust.
Creator backlink kit
Add the evidence badges to your README
Show the canonical listing, current trust and audit signals, and real Agent-Proven evidence where developers evaluate the repository.
[](https://www.openagentskill.com/skills/jparkerweb-ai-assist-project-summary)
[](https://www.openagentskill.com/skills/jparkerweb-ai-assist-project-summary)
[](https://www.openagentskill.com/skills/jparkerweb-ai-assist-project-summary/audit)
[](https://www.openagentskill.com/skills/jparkerweb-ai-assist-project-summary)Author
jparkerweb
@jparkerweb
Tags
Platform fit
Health signals
- GitHub stars
- 88
- Quality score
- 37/100
- Last GitHub push
- Aug 20, 2026
- Framework hints
- Unknown
- OpenAgentSkill views
- 2
- Install copies
- 0
- Outbound clicks
- 0
Community signal
Share whether this skill looks useful for your agent workflow. Aggregated feedback improves rankings over time.
Trust & safety
Sandbox only
- GitHub adoption88 GitHub starsCHECK
- Stars/forks activity88 stars, 12 forks; issue activity unavailable in current metadataCHECK
- Recent maintenance3d since pushPASS
- License clarityUnknownCHECK
- README/SKILL.md completenessMetadata includes enough usage and workflow contextPASS
- Dependency/runtime riskno major dependency risk hints in public metadataPASS
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