Creator · LocalSymmetry
Last updated · Aug 24, 2026
lofn-music
Run the Lofn music/audio pipeline (steps 00–11) backed by Codex — Suno-ready song packages with two-field style/exclude prompts, EMO-tagged lyrics, song guides. Use for songs, tracks, beats, lyrics, music production briefs, or "write a song with the full pipeline". Expects a Phas
Do not auto-install
Install targets
Codex install prompt
Install the "lofn-music" agent skill from https://github.com/LocalSymmetry/lofn/tree/main/.agents/skills/lofn-music. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: Run the Lofn music/audio pipeline (steps 00–11) backed by Codex — Suno-ready song packages with two-field style/exclude prompts, EMO-tagged lyrics, song guides. Use for songs, tracks, beats, lyrics, music production briefs, or "write a song with the full pipeline". Expects a Phase-0/1 orchestrator packet from the `lofn` skill; if none exists, run `lofn` first. Do NOT use for static images, video, story prose, or QA-only audits. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {"event_id":"install_<unique-id>","skill_slug":"localsymmetry-lofn-music","task":"Install lofn-music","agent":"codex","outcome":"success","install_used":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.Supply asset profile
Coding and developer agents
Code review, repo analysis, testing, CI, GitHub, DevOps, and developer workflow skills.
Scenario
GitHub automation
I need my agent to triage GitHub issues, review pull requests, and summarize repository changes.
Agent fit
Claude Code + OpenAI Agents + CLI
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add LocalSymmetry/lofn --skill lofn-music
Maintenance
fresh
Pushed today
Risk
Needs review
License is unclear
GitHub quality
22
55/100 Quality · 66/100 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
Do not auto-installTrust Score v5 found insufficient evidence for agent installation. Treat this as discovery material, not an executable recommendation.
Audit
Needs reviewA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Human review before install
Choose a stronger alternative or inspect the source manually before any install attempt.
Stars
22 GitHub stars
Repo activity
22 stars, 1 forks
Maintenance
Pushed today
License
Unknown
Install
npx skills add LocalSymmetry/lofn --skill lofn-music
Install safety
standard package or runtime install path
Permission surface
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 detected as 'Unknown', which creates compliance ambiguity regarding usage and redistribution rights.
- Financial research output is not financial advice; require human review before any live investment decision.
- License is unclear
- Low GitHub adoption signal
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.
View technical data+
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 LocalSymmetry/lofn --skill lofn-music
- Policy
- review
- Human review
- yes
Trust and risk
- Trust
- 58/100
- Audit
- 72/100
- Risk level
- Needs review
Outcome loop
- Endpoint
- /api/agent/outcome
- Event ID
- resolve
- Outcomes
- 5
Install command
npx skills add LocalSymmetry/lofn --skill lofn-musicDo not use when
- teams that need a vendor-supported SLA
- production agents without a repository review
- Low GitHub adoption signal
- Repository license is detected as 'Unknown', which creates compliance ambiguity regarding usage and redistribution rights.
- No OpenAgentSkill engagement data yet
Agent safety v2
52/100 · 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.
medium
Browser automation
Skill may drive a browser or interact with web pages.
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.
- License is unclear
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 JSON
/api/agent/resolve?task=Use%20lofn-music%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20lofn-music%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/localsymmetry-lofn-music/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 lofn-music in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20lofn-music%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/localsymmetry-lofn-music/install
Install command: npx skills add LocalSymmetry/lofn --skill lofn-music
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/localsymmetry-lofn-music/install
LLM text format
/api/skills/localsymmetry-lofn-music/install?format=text
Find alternatives
/api/skills/search?q=lofn-music&limit=3
Agent prompt
Use lofn-music for this task. Review https://www.openagentskill.com/api/skills/localsymmetry-lofn-music/install, then install with: npx skills add LocalSymmetry/lofn --skill lofn-musicRegistry 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/localsymmetry-lofn-music
LLM text
/api/registry/manifest/localsymmetry-lofn-music?format=text
Install alias
/api/registry/install/localsymmetry-lofn-music
Recommend
/api/registry/recommend?task=Use%20lofn-music%20in%20an%20agent%20workflow&limit=3
Agent fit
Research agents
Use-case tags
Platforms
Claude Code, OpenAI Agents
Audit report
Needs review · 72/100
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Needs validation for Research agents
Do a manual repository review before adding this to an agent workflow.
Role in stack
Needs validation
Primary fit
Research agents
Trust label
Needs manual review
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
- 55/100 quality profile
review first
- Low GitHub adoption signal
- Repository license is detected as 'Unknown', which creates compliance ambiguity regarding usage and redistribution rights.
- No OpenAgentSkill engagement data yet
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
Do not auto-install
Trust Score v5 found insufficient evidence for agent installation. Treat this as discovery material, not an executable recommendation.
GitHub adoption
FIX22 GitHub stars
Stars/forks activity
FIX22 stars, 1 forks; issue activity unavailable in current metadata
Recent maintenance
PASSPushed today
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 detected as 'Unknown', which creates compliance ambiguity regarding usage and redistribution rights.
- Financial research output is not financial advice; require human review before any live investment decision.
- License is unclear
- Low GitHub adoption signal
- Quality score needs review
- GitHub adoption: 22 GitHub stars
- Stars/forks activity: 22 stars, 1 forks; issue activity unavailable in current metadata
- License clarity: Unknown
- No real agent outcome reports yet
- Human review required before unattended installation
Recommended action
Choose a stronger alternative or inspect the source manually before any install attempt.
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.
Process rich media
Multimodal media
I need my agent to process images, video, or audio and extract useful information.
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.
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.
Inspect, patch, and verify code
Coding review agent
A workflow for software agents that inspect repositories, review pull requests, generate tests, and turn findings into shippable patches.
Alternative shortlist
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Overview
--- name: lofn-music description: Run the Lofn music/audio pipeline (steps 00–11) backed by Codex — Suno-ready song packages with two-field style/exclude prompts, EMO-tagged lyrics, song guides. Use for songs, tracks, beats, lyrics, music production briefs, or "write a song with the full pipeline". Expects a Phase-0/1 orchestrator packet from the `lofn` skill; if none exists, run `lofn` first. Do NOT use for static images, video, story prose, or QA-only audits. ---
# Lofn Music — Codex-backed audio pipeline
Produces Suno/Udio-ready song packages at Lofn competition grade. The creative depth lives in the legacy step files and references under `skills/music/`; this skill runs them with Codex as the engine (hybrid execution per `.agents/skills/lofn/EXECUTION.md`).
## Before you start 1. Confirm a Phase-0/1 packet exists for this run (`core_seed.md`, `04_metaprompt.md`, `05_pair_assignments.md`, `06_audio_handoff.md` with the **ICB / Panel Ledger**, and the filled `CREATIVE_CONTEXT.md`). **No packet → run the `lofn` skill first.** A real 3-panel orchestrator object is a launch prerequisite; do not self-author a shallow one. 2. Read for depth (just-in-time, not all upfront): - `skills/music/references/music_full_legacy.md` — the full tuned pipeline (authoritative) - `skills/music/references/producer_grade_suno_prompt_guide.md` + `vault/SUNO_PROMPT_CONSTRUCTION_GUIDE.md` — prompt construction - `skills/music/references/golden_songs_index.md` — pick/confirm the 2 Golden Songs **by name** in the handoff - `skills/lofn-core/refs/EMOTION_TAXONOMY.md` — the only valid source for EMO emotions - ⛔ **GOLDEN-OUTPUT QUARANTINE (`EXECUTION.md` §3):** the `suno_format_example_*.md` payloads (Triple Arch, Blue Screen, Five Wrong Colors) are **judge-side references only** — QA blind comparison, step 12, the step11-packager. They are NEVER pasted into a generating context (coordinator steps, pair subagents, step 11). An exemplar in the generator's prompt becomes a mold: the run regresses toward a diluted copy of it. Generators get the Golden Seed + the GOLDEN MOVE (below).
## The Golden Move (what generators get INSTEAD of golden songs) The 2026-07-01 regression review distilled why "Triple Arch Over Me" won, as **instructions, not an exemplar**. Every pair receives this block (it also lives in the Phase-1 handoff): 1. **Stand somewhere real.** The song is a report from ONE concrete place the body occupies — name where it stands and what the senses register there. Concept-illustration ("a metaphor about X") is the failure mode; experience-report is the move. If three runs in a row are indoors and safe, go outside. 2. **One wounding fact.** At most ONE numeric/scientific fact is sung, placed at the emotional hinge, and the lyric must RESPOND to it ("It says behold and calculate"), never recite it. All other research stays in the brief as atmosphere. 3. **The turn.** Somewhere past the midpoint, the song contradicts or complicates its opening stance — a mind changing in real time, an argument with itself the ending has to earn. A song that asserts its final emotion from line one is a corpse. 4. **Fear stays braided in.** AWE is terror-adjacent sublime, not domestic reassurance — every awe song carries a clean fear it does not resolve cheaply. 5. **Rotate the register.** Do not default to the house winner's fingerprint (crystalline female soprano / A major / ~110 BPM / frost-and-cosmos palette). Vary key, tempo, vocal register, and sonic world per run unless the personality's YAML mandates them. The house-lexicon FLAG (`vault/gates.yaml`) catches verbatim self-copying; this rule prevents the softer clone. 6. **The surface names its subject (first-listen legibility).** A stranger must be able to retell the song's scene AND subject in one sentence after ONE listen — the subject appears PLAINLY in the lyric at least once (title or an early verse), not only through metaphor. Triple Arch names its sky outright; the depth lives in the RESPONSE to the named thing, never in withholding the referent. Obliqueness about what the song is about is not depth, it is fog (2026-07-01 test slice: an AWE song about a survivor star read as being about a troubled uncle — structurally perfect, emotionally unreachable). Simple surface, complex engine: the cathedral lives UNDER a legible surface, not instead of one. This is the music equivalent of the image lane's thumbnail test, and the Somatic Gate should treat an unnameable subject as `REPAIR — FOG`.
## 🔁 THE RETURN — the sixth Golden Move rule (added 2026-07-24)
*The Scientist, after three consecutive runs: "the lyrical methods avoid rhymes, but aren't adding alliteration, consonance, or fun and interesting audio-written joys. I think it is making the music sound like we're being lectured at."*
Measured against LOFN-PRIME's own archived winners, she was right about the effect and the diagnosis is sharper than the hypothesis:
| | strict end-rhyme | repeated-line ratio | words/line | alliteration /100w | |---|---|---|---|---| | **archive winners** | **0.463** | **0.326** | 6.69 | 14.19 | | 2026-07-24 | 0.210 | 0.181 | 8.30 | 13.36 | | 2026-07-13 | 0.256 | 0.202 | 6.73 | 15.90 | | 2026-07-09 | 0.132 | 0.105 | 5.20 | 10.84 |
**Alliteration was never the problem — it is at parity, and one run beat the winners.** What collapsed was **return**: rhyme returning, and lines returning. We wrote at roughly half the winners' rate of both, in longer and more monosyllabic lines. Long plain declaratives that never come back is the prosody of *prose*, and prose delivered with conviction is a lecture.
**Song is made of returns. Texture is not structure.**
### Measure it with the shipped function, never by eye or by re-derivation `scripts/measure_soundcraft.py` → `profile_file(path)` is **the** definition. `strict_end_rhyme` = last-3-characters of each line's final word recurring within **±4 lines** (`gates.yaml → rhyme_window`). This is stated because three repair agents once reverse-engineered three different windows (±2, ±4, ±7) from a brief that named a threshold without defining it, and each honestly reported "reproduces the baseline exactly" — one song then measured 0.319 against its own window and 0.223 against the canonical one. **Never hand an agent a numeric target without the function that computes it.**
### The Rhyme Debt rule Stripping end-rhyme is a legitimate device — three of the last three runs used rhyme-*decay* as form and it worked. But **removal is not craft; it is a debt.** A pair that strips rhyme MUST name, in its step-05 isolation brief, **what returns in its place**: a refrain that recurs unchanged, a vowel spine, a rhythmic figure, an anaphoric opening, a repeated syntactic frame. *"No full end-rhyme"* with nothing declared opposite it is a **repair**, not a style.
Watch for the tell in a brief: `no rhyme` · `no metaphor` · `no dynamics` · `deliberately unpoetic diction` · `never lifting`. That is five subtractions and zero additions — a pair brief written entirely in negatives will produce a lecture no matter how good the concept is.
### Exact chorus repetition needs no defence `unique_line_ratio_floor` is chorus-exempt **by policy**, yet pair agents kept writing around it — mutating refrains pre-emptively and filing justifications (*"this is the mechanism, not a defect"*, *"recommend HUMAN WAIVE not repair"*). A flag that makes writers apologise for choruses is doing damage even when it never fires. **A byte-identical chorus is correct. Say nothing about it.**
### A PROSODY axis is now mandatory at Phase 0 The 2026-07-24 seed carried five constraint axes and **every one was semantic** (custody act · proof-gap · how the centre empties · apparatus register · temporal stance). Not one was phonetic, and the frames palette's eight LYRIC devices were all rhetorical figures — apophasis, apostrophe, anaphora — with **zero sound devices**. Sound was specified only as removals.
Every seed now carries a **SOUND / RETURN axis** as a positive vocabulary of 4–6 options, e.g.: `hard-consonant spine` · `vowel ladder that climbs across the stanza` · `internal-rhyme chain` · `sprung/uneven stress against a steady pulse` · `refrain that returns exactly` · `refrain that returns one word wrong` · `monosyllabic verse breaking into polysyllabic chorus`. Assign one per pair, distinct, same as any other axis.
## Execution (hybrid) Coordinator **00–05 inline**, then **6 pairs fan out as parallel Codex subagents** for 06–10, then **step 11 enhancement** (1 subagent/pair). Inject the full `CREATIVE_CONTEXT.md` into every step and every subagent (`EXECUTION.md` §3). Default cardinality: **6 pairs × 4 variations = 24 songs.**
### Coordinator steps (inline — you) Run each as its own pass with its own saved canonical artifact (do NOT collapse 00–05 into one):
| Step | File | Output artifact | |------|------|-----------------| | 00 | `skills/music/steps/00_Generate_Music_Aesthetics_And_Genres.md` | `step00_aesthetics_and_genres.md` (50×4 JSON) | | 01 | `skills/music/steps/01_Generate_Music_Essence_And_Facets.md` | `step01_essence_and_facets.md` | | 02 | `skills/music/steps/02_Generate_Music_Concepts.md` | `step02_concepts.md` (12 concepts) | | 03 | `skills/music/steps/03_Generate_Music_Artist_And_Critique.md` | `step03_artist_and_critique.md` | | 04 | `skills/music/steps/04_Generate_Music_Medium.md` | `step04_medium.md` | | 05 | `skills/music/steps/05_Generate_Music_Refine_Medium.md` | `step05_refine_medium.md` → **6 pairs chosen** |
**Step 05 selects INTO the six Phase-1 pair slots, never past them:** Phase 1 owns each slot's arm/genre/verse-structure; step 05 owns which of the 12 concepts fills each slot (**exactly 6** — only the Scientist downsizes, explicitly) and records the runner-up rationale plus the **cut ledger** (one line per losing concept: why it lost + one organ worth harvesting — the reserve bench for `EXECUTION.md` §7.3's REPLACE/REDIRECT routes). For dailies, Step 05 also writes a pair-specific isolation brief (`pair_{NN}_step05_isolated_brief.md`) naming that pair's unique section architecture, rhyme/line logic, hook grammar, and sonic device before any lyric generation.
### Per-pair steps (parallel subagents — one chain per pair) Give each of the 6 pair-subagents its full ICB + pair assignment + these step contracts, and have it produce all five canonical files for its pair:
| Step | File | Per-pair artifact | |------|------|-------------------| | 06 | `skills/music/steps/06_Generate_Music_Facets.md` | `pair_{NN}_step06_facets.md` | | 07 | `skills/music/steps/07_Generate_Music_Song_Guides.md` | `pair_{NN}_step07_song_guides.md` — **opens with the two pre-draft questions:** *Where is the body standing?* and *What could hurt it here?* A guide that can't answer both concretely (place + stake) is not ready to direct; three consecutive runs answering "a kitchen" and "nothing" is itself a repair signal. | | 08 | `skills/music/steps/08_Generate_Music_Generation.md` | `pair_{NN}_step08_generation.md` | | 09 | `skills/music/steps/09_Generate_Music_Artist_Refined.md` | `pair_{NN}_step09_artist_refined.md` | | 10 | `skills/music/steps/10_Generate_Music_Revision_Synthesis.md` | `pair_{NN}_step10_revision_synthesis.md` |
**Daily pair-isolation law:** in daily music, each pair's Steps 05–11 are a separate creative run. Do not let one all-pairs helper, line factory, lyric skeleton, section map, rhyme scheme, hook grammar, or production arc author multiple pairs. The pair may share validators, file writers, and the ICB; it may not share creative bones. If two pairs sound like the same song with nouns swapped, Step 11 marks `REPAIR — PAIR BLEED` and routes the affected pairs back to Step 05 isolated briefs.
**Describe-render self-check (one capped pass, reuses the existing max-3-attempt loop — `EXECUTION.md` §4).** Before a pair returns its step-10 package, it predicts in 2–3 sentences what its Suno prompt would actually **PRODUCE** — the liter
Technical details
- Version
- 1.0.0
- License
- Unknown
- Last updated
- Aug 24, 2026
- Published
- Aug 24, 2026
Decision snapshot
Needs validation
recent repository activity
Audit
Install review
Install and adoption review
- Security
- 74/100
- 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 lofn-music, ready for a manual X post.
A practical pick for design or creative work: lofn-music: Run the Lofn music/audio pipeline (steps 00–11) backed by Codex — Suno-ready song packages with two-field style/exclude pro... 22 stars https://www.openagentskill.com/skills/localsymmetry-lofn-music?ref=x
Optional reply with install command
Listing + install path for lofn-music: https://www.openagentskill.com/skills/localsymmetry-lofn-music?ref=x Install: npx skills add LocalSymmetry/lofn --skill lofn-music
Listing source
Registry indexed
This listing was indexed from public sources and is not marked official until a maintainer claim is approved.
- Creator
- LocalSymmetry
- Source
- LocalSymmetry/lofn
- 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 LocalSymmetry 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.
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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/localsymmetry-lofn-music)
[](https://www.openagentskill.com/skills/localsymmetry-lofn-music)
[](https://www.openagentskill.com/skills/localsymmetry-lofn-music/audit)
[](https://www.openagentskill.com/skills/localsymmetry-lofn-music)Author
LocalSymmetry
@localsymmetry
Tags
Platform fit
Health signals
- GitHub stars
- 22
- Quality score
- 32/100
- Last GitHub push
- Aug 24, 2026
- Framework hints
- Unknown
- OpenAgentSkill views
- 0
- 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
Do not auto-install
- GitHub adoption22 GitHub starsFIX
- Stars/forks activity22 stars, 1 forks; issue activity unavailable in current metadataFIX
- Recent maintenancePushed todayPASS
- 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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