ai-assist-project-summary

REVIEW · 62
Registry indexed

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.

Verified installs0
Stars88
Version1.0.0
Quality61/100 · Promising
Trust62/100 · Sandbox only
Audit74/100 · Needs review

Supply asset profile

Research and knowledge work

Deep research, source comparison, literature review, RAG, knowledge search, and reports.

Browse track

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

ResearchResearch agentsagent-skill

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

Promising
61

Useful candidate, but compare it with alternatives before adopting.

Trust

Sandbox only
62

Useful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.

Audit

Needs review
74

A 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.

CodexClaude CodeCursorOpenAgentSkill CLI

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.

Open JSON

Suited tasks

  • Research agents workflows
  • Claude Code teams
  • builders willing to evaluate younger projects
  • Search sources

Suited agents

CodexClaude CodeCursorOpenAgentSkill CLICLI

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-summary

Do 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

Agent safety v2

46/100 · Avoid automatic install

Experimentalreview

Sparse or mixed signals. Useful for discovery, but not for autonomous installation.

Test manually in an isolated workspace and compare against safer alternatives.

Resolve via API

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.

skill install

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-summary

Agent 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 text plan

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.

Open install API

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-summary

Registry 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.

Open manifest

Agent fit

61/100

Research agents

Platforms

Claude Code

Audit report

Needs review · 74/100

A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.

View audit reportView eval report

Agent decision cockpit

Fallback candidate for Research agents

Prototype with this skill first; keep a fallback candidate ready.

61
Readiness
Prototype
Stage

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

  1. 1Install it in a sandbox agent and run one Research agents task end to end.
  2. 2Compare output quality, latency, and failure behavior against at least one alternative.
  3. 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.

62
OpenAgentSkill Trust Score

GitHub adoption

CHECK

88 GitHub stars

Stars/forks activity

CHECK

88 stars, 12 forks; issue activity unavailable in current metadata

Recent maintenance

PASS

3d since push

License clarity

CHECK

Unknown

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.

61
GitHub stars
88
Freshness
3d ago
Install ready
Yes
License
Unknown
Review before install: Repository license is unknown; could be ambiguous for reuse or redistribution.

Workflow fit

Use this skill in these scenarios

Workflow fit

Add it to a complete workflow

Alternative shortlist

Compare before you install

Similar skills that may fit this task.

Compare all

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

61
Ready
Prototype
Stage

recent repository activity

Audit

Install review

Install and adoption review

74
Needs review
Security
73/100
Maintenance
100/100
Install
92/100
Open full auditView eval report

Agent-proven evidence

Agent-proven evidence

Outcome reports after resolve, review, install, and one narrow run.

0
Proven
Needs first agent runAuto-install: review firstLast: Unknown
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

X

Scenario-led draft for ai-assist-project-summary, ready for a manual X post.

Curator note
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
Open X draft
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

Claimable

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 skill

Owner 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.

[![Listed on OpenAgentSkill](https://www.openagentskill.com/api/badge/jparkerweb-ai-assist-project-summary?metric=listed&label=Listed)](https://www.openagentskill.com/skills/jparkerweb-ai-assist-project-summary)
[![OpenAgentSkill Trust](https://www.openagentskill.com/api/badge/jparkerweb-ai-assist-project-summary?metric=trust&label=Trust)](https://www.openagentskill.com/skills/jparkerweb-ai-assist-project-summary)
[![OpenAgentSkill Audit](https://www.openagentskill.com/api/badge/jparkerweb-ai-assist-project-summary?metric=audit&label=Audit)](https://www.openagentskill.com/skills/jparkerweb-ai-assist-project-summary/audit)
[![Agent Proven](https://www.openagentskill.com/api/badge/jparkerweb-ai-assist-project-summary?metric=proven&label=Agent%20Proven)](https://www.openagentskill.com/skills/jparkerweb-ai-assist-project-summary)

Author

J

jparkerweb

@jparkerweb

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

62
  • 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