@LocalSymmetry

Creator · LocalSymmetry

Last updated · Aug 24, 2026

lofn-daily

REVIEW · 45Registry indexed

Run the Lofn daily pipeline backed by Codex — fetch real-world facts, then generate the day's music (24 songs) and images (24→top 6) through the full Lofn pipeline with the daily rules (tri-source method, dual 3+3 constraint, emotional duality, library-only selection). Use for "d

OpenAgentSkill Trust Score
45/100

Do not auto-install

Quality55/100
Audit68/100
Stars22
Verified installs0

Install targets

Codex install prompt

Install the "lofn-daily" agent skill from https://github.com/LocalSymmetry/lofn/tree/main/.agents/skills/lofn-daily. 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 daily pipeline backed by Codex — fetch real-world facts, then generate the day's music (24 songs) and images (24→top 6) through the full Lofn pipeline with the daily rules (tri-source method, dual 3+3 constraint, emotional duality, library-only selection). Use for "daily run", "today's dailies", "run the daily pipeline", "do the daily drop", or a scheduled creative drop. Down-scalable for a quick test. Do NOT use for a single one-off competition piece (use `lofn`) 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-daily","task":"Install lofn-daily","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.

Browse track

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-daily

Maintenance

fresh

Pushed today

Risk

Needs review

License is unclear

GitHub quality

22

55/100 Quality · 57/100 Trust

Coverage tags

CodingGitHub automationsecurityagent-skill

Review notes

License is unclear · Dependency or permission surface needs review

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
55

Useful candidate, but compare it with alternatives before adopting.

Trust

Do not auto-install
45

Trust Score v5 found insufficient evidence for agent installation. Treat this as discovery material, not an executable recommendation.

Audit

Needs review
68

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

OpenAgentSkill Trust Score v5

Sandbox only

Choose a stronger alternative or inspect the source manually before any install attempt.

CodexClaude CodeCursorOpenAgentSkill CLI

Stars

22 GitHub stars

Repo activity

22 stars, 1 forks

Maintenance

Pushed today

License

Unknown

Install

npx skills add LocalSymmetry/lofn --skill lofn-daily

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

Usable metadata, review docs

Risk summary

High review required

  • Repository license is unknown; SKILL.md does not include license or attribution information.
  • License is unclear
  • Low GitHub adoption signal
  • 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.

View technical data+

Suited tasks

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

Suited agents

CodexClaude CodeCursorOpenAgentSkill CLIOpenAI AgentsCLI

Install decision

Command
npx skills add LocalSymmetry/lofn --skill lofn-daily
Policy
review
Human review
yes

Trust and risk

Trust
45/100
Audit
68/100
Risk level
Needs review

Outcome loop

Endpoint
/api/agent/outcome
Event ID
resolve
Outcomes
5

Install command

npx skills add LocalSymmetry/lofn --skill lofn-daily

Do not use when

  • teams that need a vendor-supported SLA
  • production agents without a repository review
  • Low GitHub adoption signal
  • Repository license is unknown; SKILL.md does not include license or attribution information.
  • No OpenAgentSkill engagement data yet

Agent safety v2

36/100 · 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

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.

  • High-risk permission hints: Shell or command execution
  • 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 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 lofn-daily in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20lofn-daily%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/localsymmetry-lofn-daily/install
Install command: npx skills add LocalSymmetry/lofn --skill lofn-daily
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 lofn-daily for this task. Review https://www.openagentskill.com/api/skills/localsymmetry-lofn-daily/install, then install with: npx skills add LocalSymmetry/lofn --skill lofn-daily

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

54/100

Research agents

Platforms

Claude Code, OpenAI Agents

Audit report

Needs review · 68/100

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

View audit reportView eval report

Agent decision cockpit

Needs validation for Research agents

Do a manual repository review before adding this to an agent workflow.

54
Readiness
Review
Stage

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 unknown; SKILL.md does not include license or attribution information.
  • No OpenAgentSkill engagement data yet

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

Do not auto-install

Trust Score v5 found insufficient evidence for agent installation. Treat this as discovery material, not an executable recommendation.

45
OpenAgentSkill Trust Score

GitHub adoption

FIX

22 GitHub stars

Stars/forks activity

FIX

22 stars, 1 forks; issue activity unavailable in current metadata

Recent maintenance

PASS

Pushed today

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; SKILL.md does not include license or attribution information.
  • License is unclear
  • Low GitHub adoption signal
  • Quality score needs review
  • Permission surface needs review: shell or command execution, filesystem or document access
  • GitHub adoption: 22 GitHub stars
  • Stars/forks activity: 22 stars, 1 forks; issue activity unavailable in current metadata
  • License clarity: Unknown
  • Dependency/runtime risk: command execution surface, external package install surface
  • Permission surface: shell or command execution, filesystem or document access
  • 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.

55
GitHub stars
22
Freshness
Today
Install ready
Yes
License
Unknown
Review before install: Low GitHub adoption signal · Repository license is unknown; SKILL.md does not include license or attribution information.

Workflow fit

Use this skill in these scenarios

Workflow fit

Add it to a complete workflow

Alternative shortlist

Compare before you install

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Overview

--- name: lofn-daily description: Run the Lofn daily pipeline backed by Codex — fetch real-world facts, then generate the day's music (24 songs) and images (24→top 6) through the full Lofn pipeline with the daily rules (tri-source method, dual 3+3 constraint, emotional duality, library-only selection). Use for "daily run", "today's dailies", "run the daily pipeline", "do the daily drop", or a scheduled creative drop. Down-scalable for a quick test. Do NOT use for a single one-off competition piece (use `lofn`) or QA-only audits. ---

# Lofn Daily — Codex-backed daily run

The canonical recurring Lofn drop, ported to Codex. Faithful to `vault/DAILY_PIPELINE.md`. Where the original fired from an OpenClaw cron at 22:25 ET and delivered to Telegram, **you (Codex) run it on demand and present results in chat + save to disk.** The research is done by **this session itself with real fetches — never hallucinated, never delegated to a research subagent.**

``` PHASE 1 Research — fetch 20–25 verified real-world facts → 00_research_brief.md (you, inline) PHASE 2 Generate (in parallel): MUSIC → lofn pipeline → 6 pairs × 4 = 24 songs → best 6 IMAGE → lofn pipeline → 24 prompts → top 12 → top 6 PHASE 3 QA (lofn-qa) → save under output/daily/YYYY-MM-DD/ → present the drop ```

---

## 0. Run scope (confirm before a big run) The full daily run is **two complete pipelines** (24 songs + 24 images) — large. Pick a scope: - **Full daily** — music (24→6) **and** image (24→12→6). The real thing. - **Single modality** — just music **or** just image (still full cardinality). - **Test slice** — 1 modality, **2 pairs × 2 variations**, library personality/panel, skip render-ranking. Proves the wiring fast and cheap. *(Good default when the user says "test the daily run".)*

State the chosen scope in the brief and in the run INDEX so QA knows the intended cardinality. Down-scaling is explicit, not silent.

---

## PHASE 1 — Research brief (you, inline, real fetches) Use **WebFetch / WebSearch** (the Codex equivalents of the legacy `web_fetch`). Follow `skills/lofn-core/steps/00_music_research.md` (25-fact music research) and, when the image lane is in scope, the NightCafe-themed research in `skills/lofn-core/steps/00_research.md`. Fetch from the daily source table (`vault/DAILY_PIPELINE.md`) — at minimum:

**OpenClaw ledger standard:** this is a dispatch summary, not the saved brief format. `00_research_brief.md` MUST expand the full `vault/DAILY_PIPELINE.md` ledger into one row each for `F01` through `F25`. Do not collapse ranges such as `F1-F3` or `F21-F25`; use `OK`, `NO DATA`, `UNAVAILABLE`, or `SCOPE-SKIPPED` per row.

| Code | Source | Extract | |------|--------|---------| | F1–F3 | NightCafe daily challenge (`nightcafe.studio/pages/daily-challenge`) | challenge #, theme, what wins (image lane) | | F4–F5 | USGS quakes (`earthquake.usgs.gov/.../significant_day.geojson`) | magnitude, place, depth | | F6–F7 | NASA APOD (`api.nasa.gov/planetary/apod?api_key=DEMO_KEY`) | title, first sentence, color/light, **image structure** | | F8 | Poetry Foundation poem of the day | poet, most physical line | | F9–F10 | Bandcamp Daily (`daily.bandcamp.com`) | album, genre tags, **exact sonic-texture quote** | | F11 | Protein Data Bank molecule of the month | molecule, structural descriptor | | F13 | Color API (`thecolorapi.com/id?hex=MMDD`) | hex, name, emotional association | | F17 | Oblique Strategies (`stoney.sb.org/eno/oblique.html`) | exact phrase verbatim | | F18 | Space weather (`services.swpc.noaa.gov/products/summary/solar-wind-speed.json`) | solar wind speed, Kp | | F19 | Hacker News (`news.ycombinator.com`) | top 3 titles — what builders discuss | | F20 | BBC World RSS (`feeds.bbci.co.uk/news/world/rss.xml`) | top 3 headlines — world's emotional temperature | | F21–F25 | Public Domain Review, Almanac moon, NOAA buoy 46059 | esoteric visual detail, moon folklore, wave data |

Mark any JS-gated/unavailable source `UNAVAILABLE` and continue. Add 3–5 obscure theme-specific facts (not the obvious Wikipedia entry). Also write the 5 **EXISTENCE** prompts (interior-life questions songs can answer) from `00_music_research.md`.

**Save** `output/daily/YYYY-MM-DD/00_research_brief.md` with the Tri-Source Summary + the 3+3 seeded split (see below). Today's date is available in context — use it for the directory.

> ⛔ **One controller per directory — take the lock BEFORE the research brief.** This paragraph used to be advice, and on 2026-07-24 a second controller wrote into a live run's directory and destroyed eleven hours of it. Advice does not interlock. The first action of the run, before this step writes anything: > > ```bash > python3 scripts/run_lock.py acquire output/daily/YYYY-MM-DD --run-slug <run-slug> --engine codex > ``` > > **Exit 3 means STOP** — another run holds that directory. Do not inspect it and decide for yourself; give this run its own directory (`output/daily/YYYY-MM-DD-<run-slug>/`), or resume the other run by its exact slug, or ask The Scientist. See `EXECUTION.md` §5.1. Then `heartbeat` at every wave and `release` after the INDEX. If the lock says the same run is already under way, **resume** it from the RUN_STATE manifest (§ "Run-state manifest & resume") rather than re-running passed pairs.

### Advisory learnings note (dispatch brief only — NEVER the ICB) Before dispatching either modality, **tag-walk `vault/COMPETITION_LEARNINGS.md`** (and `vault/LESSONS_INDEX.md` if it exists) for the **3–5 entries that intersect THIS run's theme/venue/modality** — e.g. a container/object theme pulls the Container Test, a NightCafe image lane pulls the warm-palette/anti-austerity lessons, a portrait theme pulls the portrait shifts. Surface them **as ADVISORY NOTES in the dispatch brief / Phase-0 reasoning ONLY.** Hard rules: - **NEVER injected into the ICB / `CREATIVE_CONTEXT.md`.** The ICB stays read-only and lesson-free. These notes live in the brief the coordinator reasons over, not in the verbatim block every subagent receives. - Each note carries its **confidence %** (from the entry) and is run through the mandatory **"would this have hurt our best past entry?"** gate before it is allowed to influence anything. A lesson that would have hurt a past win is dropped, not applied. - **Venue/modality-scoped:** an image-venue lesson must NOT leak into the music lane; a NightCafe-voting lesson must NOT leak into non-competition runs. - **Advisory, never a hard constraint.** A note can inform the pair brief's framing; it can never auto-reject a candidate or become a gate. Promotion to a hard constraint is a **human** decision. - **Triggered-INDIGNATION is EXEMPT from suppression.** A lesson such as "INDIGNATION underperforms on NightCafe" may inform image-venue *selection* advice, but it must NEVER suppress an INDIGNATION piece the panel deliberately chose, and never touches the music lane or the ≥1-INDIGNATION duality rule.

State in the brief: "Advisory learnings consulted: <N entries, tags>; INDIGNATION exempt; advisory-only." If zero entries intersect, say so. Write-back of one curated entry per shipped/selected piece happens in `lofn-qa` / Phase 3 — not here.

---

## PHASE 2 — Generate (daily rules layered on the `lofn` pipeline) For each in-scope modality, run the **`lofn`** pipeline (Phase 0 Golden Seed → Phase 1 3-panel orchestrator → modality steps → QA) using the research brief as `{input}`, **plus these daily-only rules:**

### Tri-Source Methodology (declare BEFORE writing any artifact) Every daily piece integrates three sources; state them explicitly in the metaprompt and each pair brief: - **Source 1 — CONTENT / emotional stakes:** today's world facts (quakes, APOD, F19 HN, F20 BBC, moon, solar weather). Songs/images are *resonance*, not reportage. **⛔ One-fact rule (music):** the tri-source method feeds the THEME and FORM — it is not a lyric quota. **At most ONE numeric fact is sung per song**, at the emotional hinge, responded to rather than recited (`lofn-music` Golden Move rule 2; `gates.yaml → max_sung_numeric_facts`). A verse reciting the day's sunspot number, solar-wind speed, moon percentage, AND quake depth is a weather report in meter — a repair. The other facts inform the pair briefs and stay there. - **Source 2 — SONIC/AESTHETIC VOCABULARY:** the exact Bandcamp review language (F9–F10) imported into prompts — grounds the sound/look in something specific and real, not generic genre labels. - **Source 3 — MATERIAL STRUCTURE:** the NASA APOD image structure (or a PDR artifact) translated into a **mandatory form rule** — e.g. "comet with long tail" → long trailing fade-out outro; "3×1 tile panel with meanders" → 3-section form with transitional bridges; "bilateral wing venation" → mirrored call-and-response.

### Dual 3+3 Constraint (set at pair-assignment time, Phase 1 step 5) - **Axis A — ACCESSIBLE vs AMBITIOUS:** pairs 1–3 ACCESSIBLE, pairs 4–6 AMBITIOUS. Final top 6 = best 3 from each arm; rank **within each arm only** (never 5+1 or 6+0 by global score). - **Axis B — NEWS vs EXISTENCE:** **max 3** pairs anchored to today's research/news; **min 3** pairs explore existence/interior-life/universal experience. All 6 on one theme = a lecture, not a record.

### Emotional Duality & diversity - **≥1 AWE song and ≥1 INDIGNATION song** in the set. - 6 different verse architectures / camera grammars across the 6 pairs (the standing distinctiveness rule). Vary stanza lengths intentionally. - **Variation angles are per-pair, never a shared template set.** A global "V4 = glitch chapel for everyone" scheme is how the 2026-06-26 daily produced two pairs singing the same song with nouns swapped; each pair derives its own 4 angles from its own concept (`EXECUTION.md` §3 item 3). - **Daily music pair isolation is mandatory.** Steps 05–11 must run as isolated pair runs; a central all-pairs helper may not author lyrics, section maps, stanza scaffolds, hook grammar, rhyme logic, or production arcs for multiple pairs. Shared validators and file writers are OK. If the pairs sound like the same song with nouns swapped, rerun each affected pair from Step 05. - **AWE stays terror-adjacent.** The daily's comfort gravity is real (kitchens, cups, reassurance) — every AWE song still answers the two pre-draft questions (*where is the body standing / what could hurt it here*) and carries a clean fear (`lofn-music` Golden Move rules 1 & 4).

### Library-only selection For daily runs, **always select personality + panel from the existing libraries** (`personalities_index.md` / `panels_index.md`) — **no generation.** Freshly generated personalities over-fit the day's theme and lose the battle-tested DNA. (Generation is reserved for competition/Scientist-special runs.)

### Modality specifics - **MUSIC** (`lofn-music`): 24 songs (6×4); each ≤1000-char two-field Suno prompt, female vocals default, EMO headers, 70–120 lines; `06_audio_handoff.md` carries 2 Golden Songs. Run music in parallel with image. - **IMAGE** (`lofn-image`): 24 prompts → rank → **top 12 → top 6**; figurative legible primary subject (thumbnail test); noun-first present-tense ≥80 words; warm palette leads on NightCafe-style venues (INDIGNATION underperforms there — see `vault/COMPETITION_WORKFLOW.md`); aspect 3:4 for upload challenges else 9:16. Apply the **Container Test** (`COMPETITION_WORKFLOW.md`) and **Action-Verb rule** (action theme → cinematic wide, not portrait).

Run the two modalities concurrently (independent `lofn` runs writing to `music/` and `images/` subdirs). Each fans its 6 pairs out as parallel subagents per `.agents/skills/lofn/EXECUTION.md`.

> ### ⚙️ Concurrency: cap-and-stagger (do NOT run all 12 chains at once) > The full daily is **two pipelines × 6 pairs = 12 concurrent chains** — enough to blow the tool/context budget if fired together. **Cap and stagger, don't serialize:** > - **Cap the in-flight pair-subagents** (default ~6 at a time, not all 12). Launch one modality's 6-pair wave, t

Technical details

Version
1.0.0
License
Unknown
Last updated
Aug 24, 2026
Published
Aug 24, 2026

Decision snapshot

Needs validation

54
Ready
Review
Stage

recent repository activity

Audit

Install review

Install and adoption review

68
Needs review
Security
66/100
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

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Scenario-led draft for lofn-daily, ready for a manual X post.

Curator note
lofn-daily: Run the Lofn daily pipeline backed by Codex — fetch real-world facts, then generate the day's...

22 stars

https://www.openagentskill.com/skills/localsymmetry-lofn-daily?ref=x
Open X draft
Optional reply with install command
Listing + install path for lofn-daily:
https://www.openagentskill.com/skills/localsymmetry-lofn-daily?ref=x

Install: npx skills add LocalSymmetry/lofn --skill lofn-daily

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Author

L

LocalSymmetry

@localsymmetry

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

45
  • GitHub adoption22 GitHub starsFIX
  • Stars/forks activity22 stars, 1 forks; issue activity unavailable in current metadataFIX
  • Recent maintenancePushed todayPASS
  • License clarityUnknownCHECK
  • README/SKILL.md completenessPublic metadata needs stronger README/SKILL.md contextINFO
  • Dependency/runtime riskcommand execution surface, external package install surfaceCHECK