Agent skill

Idea Pipeline

by aeonfun in aeonfun/aeon

Execution-gap audit - cross-references the startup idea backlog against shipped skills, prototypes, and cross-repo PRs, surfacing the top 3 ideas to build next by narrative and operator fit.

MITAuto-check passed

Install Idea Pipeline

skills CLI
$ npx skills add aeonfun/aeon --skill idea-pipeline -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install aeonfun/aeon idea-pipeline --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/aeonfun/aeon.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/idea-pipeline .claude/skills/idea-pipeline && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
idea-pipeline
GitHub stars
767
Token cost
~3.5k tokens
SKILL.md length
1,482 words
Files
1
Skills in repo
82
Repo updated
First seen
Licence
MIT

At a glance

Execution-gap audit - cross-references the startup idea backlog against shipped skills, prototypes, and cross-repo PRs, surfacing the top 3 ideas to build next by narrative and operator fit.

  • Works in 11 steps: Force-reply interception — pick: /… → Load the idea backlog → Load screening results → …
  • SKILL.md covers Why this skill exists, Steps, Required Env Vars and Network Note
  • Calls gh; reaches github.com; needs GITHUB_TOKEN

What it does

Idea Pipeline is an agent skill from aeonfun/aeon. Execution-gap audit - cross-references the startup idea backlog against shipped skills, prototypes, and cross-repo PRs, surfacing the top 3 ideas to build next by narrative and operator fit.

Its SKILL.md is about 3.5k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

The repository describes itself as: The most autonomous AI agent framework: runs unattended on GitHub Actions, self-healing skills, drives Claude Code, Grok, Codex & more. No approval loops. Configure once, forget… The licence is MIT.

Example prompts

  • “/idea-pipeline”

Workflow steps

11 steps, taken from the step headings in SKILL.md.

  1. Force-reply interception — pick: / offer: (run FIRST, before anything else)
  2. Load the idea backlog
  3. Load screening results
  4. Check execution — what's been built
  5. Cross-reference: idea vs execution
  6. Load narrative context
  7. Score unexecuted ideas for "build this week"
  8. Format and write the report
  9. Decide whether to notify
  10. Format and send notification
  11. Log to memory

What it can do on your machine

Read from SKILL.md and the folder at commit c0cb7c4. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • gh

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • github.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • GITHUB_TOKEN

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Idea Pipeline loads about 3.5k tokens when it runs. Until then it costs about 51 tokens; SKILL.md has 1,482 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~51
When it runs · the whole SKILL.md, loaded when a task matches
~3.5k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from aeonfun/aeon at commit c0cb7c4, republished under its MIT licence (© aeonfun). 1,482 words, ~3,548 tokens.

Download SKILL.mdSave it as .claude/skills/idea-pipeline/SKILL.md (or your agent's skills folder).
name
idea-pipeline
description
Execution-gap audit - cross-references the startup idea backlog against shipped skills, prototypes, and cross-repo PRs, surfacing the top 3 ideas to build next by narrative and operator fit.
metadata.category
productivity
metadata.tags
meta, creative

${var} — Optional theme filter (e.g. "crypto", "AI agents", "consumer"). If empty, scans all ideas. A pick:<id|name> value (from the "build next?" force-reply — e.g. pick:2 or pick:Onchain reputation) instead marks that idea as chosen-to-build in the backlog and ends, skipping the audit — see step 0. offer:<owner/repo or issue-url> directly offers a confirmed owned target through the same Telegram reply boundary, also ending before the audit.

Today is ${today}. Read memory/MEMORY.md before starting. If soul/SOUL.md + soul/STYLE.md exist and are populated, read them to ground "operator fit" scoring; otherwise score on the idea's general buildability and timing alone.

Why this skill exists

idea-forge validate evaluates ideas. Nothing tracks execution. Backlogs of dozens of ideas accumulate — some validated, most unscreened — with zero visibility into which ones have been acted on vs which are rotting. This skill gives that view: pipeline size, execution rate, and the 3 ideas closest to being buildable right now.

Steps

0. Force-reply interception — pick:<idea> / offer:<target> (run FIRST, before anything else)

If ${var} starts with offer:, strip and trim the remainder. Accept only owner/repo or https://github.com/owner/repo/issues/N, normalize it to owner/repo, and require gh api "repos/$repo" --jq '.permissions.push // false' to return true. Invalid, inaccessible, or API-failed targets get a plain rejection notification and end without a force reply. For a confirmed target, execute this exact command with Bash. Describing or printing the command is not delivery:

bash
./notify "Which owned repository or issue should Aeon Engineer use? Reply with ${target}." \
  --force-reply --placeholder "${target}" \
  --context "dev-loop::ship"

After the command exits zero, require at least one non-empty JSON payload under ${AEON_PENDING_DIR}/notify-queue/ and that payload's .reply_markup.force_reply == true. A queued payload alone isn't enough — notify.sh queues one even when the inbound Messages workflow is disabled, but in that case sends the prompt as plain text (reply_markup:null) with no reply routing, so the operator's answer would never come back to this skill. If the command fails, the payload is absent, or force_reply isn't true, end with FORCE_REPLY_MISSING: dev-loop::ship target=<target> and do not claim the prompt was offered. Only after both checks pass, log FORCE_REPLY_OFFERED: dev-loop::ship target=<target> under ### idea-pipeline, then end. This is an explicit operator-invoked producer path and still does not dispatch the chain until the operator replies.

Otherwise, if ${var} starts with pick:, this run is the operator answering the "which idea to build next?" force-reply — do not run the normal audit. Handle it and end:

  1. Strip the prefix: sel="${var#pick:}", then trim surrounding whitespace. The remainder may contain colons/spaces — keep them.
  2. If sel is empty, send a plain re-ask (no force-reply) and end: ./notify "Which idea should I mark as next to build? Reply with its name or backlog number."
  3. Read the shared backlog memory/topics/startup-ideas.md. If it's missing or has no idea rows, ./notify "No idea backlog yet — nothing to mark. Run idea-forge generate to fill it first." and end.
  4. Resolve sel to exactly one idea row in the table (columns | date | name | one-liner | fit | T+F+E |):
    • By name (preferred): case-insensitive exact match on the name cell; else fuzzy — the row whose name shares the most significant words with sel, or where sel is a substring of the name (or vice-versa). Require one clear best match.
    • By number: if sel is a bare integer N and no name matches, take the Nth data row (1-based, in file order).
    • If nothing matches, or two rows tie with no clear winner, send a plain re-ask listing 3–5 candidate names and end: ./notify "Couldn't find an idea matching \"<sel>\". Reply with the exact name or backlog number. Candidates: <name1>, <name2>, <name3>."
  5. Mark it chosen-to-build — the shared marking convention (identical in idea-forge): append ✓ selected ${today} to the end of that row's name cell, keeping the table pipes intact. If the cell already carries a ✓ selected marker, leave it (idempotent) — it's already queued.
  6. Do not try to infer a GitHub target from the row. The backlog's row schema (columns | date | name | one-liner | fit | T+F+E |) never carries a repo or issue reference, so a per-row target lookup here would never match a real row. offer: (step 0) is the only path from a marked idea to a dev-loop dispatch — explicit and push-permission-gated on purpose.
  7. Confirm with a short ./notify (keep it clean — no test/trace/ping/debug substrings): ./notify "Marked \"<idea name>\" as next to build — flagged in the backlog. Run /feature or /deploy-prototype on it when you're ready, or reply with: offer:<owner/repo> to have Aeon Engineer start on it directly." Do not auto-dispatch any skill — marking chosen is the safe action.
  8. Log to memory/logs/${today}.md under a ### idea-pipeline heading: - IDEA_PIPELINE_PICK: marked "<idea name>" as chosen-to-build (from a pick: reply).
  9. End the run. Do not proceed to step 1 or run the audit.
1. Load the idea backlog

Read memory/topics/startup-ideas.md. If it doesn't exist, log IDEA_PIPELINE_SKIP: no backlog at memory/topics/startup-ideas.md and stop — there's nothing to audit.

Parse the ideas table: extract name, one-liner, category/vertical, and date added for each idea. Total = N_total.

2. Load screening results

Read memory/topics/startup-ideas-screened.md (create if missing — empty table header only).

Extract ideas that have been screened. N_screened = count of rows.

From screened ideas, note those with viability >= 9 (high-potential). These are the priority pipeline.

3. Check execution — what's been built

Scan skills directory:

bash
ls skills/

Collect the list of skill directory names. These are "executed ideas" in the agent space.

Scan cross-repo PRs by the operator and their bot accounts. Read memory/topics/git-identities.md if present (operator-defined list of GitHub usernames to scan). Fall back to the workflow's GITHUB_ACTOR if no list is configured.

bash
gh pr list --author ${USERNAME} --state merged --limit 30 --json title,url,mergedAt

Scan deployed prototypes: read memory/topics/prototypes.md (or memory/topics/vercel.md) if either exists. Treat any project flagged as a prototype/MVP as a shipped idea.

Scan recent builds: read the last 14 days of memory/logs/ and collect any BUILD_SKILL_OK, CREATE_SKILL_OK, or DEPLOY_PROTOTYPE_OK entries.

Show full SKILL.md (555 more words)Show less
4. Cross-reference: idea vs execution

For each idea in the full backlog:

  • Check if any skill name or PR title contains keywords from the idea name/one-liner (fuzzy keyword match — at least 2 significant words overlap, or the core concept is clearly represented)
  • Classify as: executed (clear match found) or unexecuted

N_executed = count of ideas with a clear match. N_gap = N_total − N_executed.

5. Load narrative context

Read memory/topics/market-context.md if present for current narrative keywords (tokens trending, tech themes, regulatory signals).

Read recent logs for any narrative signals (last 3 days).

Compile a list of 8–12 active narrative keywords (e.g. "agent payments", "RWA", "prediction markets", "privacy coins"). If no market-context source exists, derive keywords from recent digest, narrative-tracker, or github-trending outputs.

5b. Load builder-ecosystem signal

Read memory/topics/ecosystem.md if it exists (written by the retired builder-map skill, so usually absent; skip this step when it is). This is the second-stream feed — "who's adopting the watched stack" becomes idea fodder.

Extract two things:

  • Underserved categories — Builder Categories with 0 or 1 known builders in the ecosystem map. Example: "social-sim" with no entries = an opening for a sim-prototype.
  • Adjacent verticals — non-obvious verticals with active builders. Verticals that already crossed over tell you which directions the stack travels well.

Compile:

  • underserved_categories — list of 2–5 categories with thin builder coverage
  • adjacent_verticals — list of 2–4 non-obvious verticals with active builders

If memory/topics/ecosystem.md doesn't exist yet, skip this step and log idea_pipeline: ecosystem_feed=unavailable in step 10. Do not block the run.

6. Score unexecuted ideas for "build this week"

For each UNEXECUTED idea, compute a priority score:

priority = narrative_fit + operator_fit_estimated + recency_bonus + ecosystem_gap_bonus

narrative_fit:          0–4 (count of active narrative keywords that appear in idea name/one-liner/category; cap at 4)
operator_fit_estimated: 0–2 — read `soul/SOUL.md` if present; +2 if the idea matches the operator's stated themes, +1 if it's solo-buildable AND adjacent to current work, 0 otherwise. If no soul file, score 0 here and let other factors decide.
recency_bonus:          2 if added in last 14 days; 1 if last 30 days; 0 otherwise
ecosystem_gap_bonus:    3 if idea's category matches an `underserved_category` from step 5b; 2 if it matches an `adjacent_vertical`; 0 otherwise

Tie-break preference when scores match: ideas that fill an underserved-category gap > ideas that hit a hot narrative. The ecosystem signal is structural (where the stack is going); narratives rotate.

If ${var} is set, additionally filter to ideas whose category/text matches ${var}.

Sort descending. Pick top 3. For each pick, in step 7's Why now: line, name the ecosystem signal explicitly if ecosystem_gap_bonus > 0 (e.g. "no builders on the stack in this category yet" or "adjacent-vertical adoption arc").

7. Format and write the report

Write to output/articles/idea-pipeline-${today}.md:

markdown
# Idea Pipeline — ${today}

**Total ideas:** N_total | **Screened:** N_screened | **Executed:** N_executed | **Gap:** N_gap

## Build This Week

### 1. [Idea Name]
**One-liner:** [one-liner from backlog]
**Why now:** [1–2 sentences connecting to active narratives or ecosystem signal]
**Operator fit:** [why this fits the operator's stack/worldview — derived from soul/SOUL.md if present, otherwise the idea's general buildability]
**Execution path:** [one sentence on fastest way to build — skill, prototype, or external PR]

### 2. [Idea Name]
...

### 3. [Idea Name]
...

## Execution Log
Ideas already shipped (skill/prototype/PR match found):
- [executed idea] → [matching skill name or PR URL]
- ...

## High-Potential Unscreened
Top 3 ideas not yet screened by `idea-forge validate` that look most promising by keyword signal alone:
- [idea] — [one-liner]
- ...

---
*Source: memory/topics/startup-ideas.md | Generated by idea-pipeline*
8. Decide whether to notify

Always notify.

9. Format and send notification

Write to .pending-notify-temp/idea-pipeline-${today}.md (create dir if needed), then:

bash
mkdir -p .pending-notify-temp
./notify -f .pending-notify-temp/idea-pipeline-${today}.md

Notification format — match the operator's voice if soul files are populated, otherwise direct and neutral:

idea pipeline — ${today}

${N_total} ideas. ${N_screened} screened. ${N_executed} executed. ${N_gap} waiting.

build this week:

1. [Idea Name] — [one-liner]
   why now: [1 sentence on timing/narrative fit]
   path: [skill / prototype / external-PR in ~N days]

2. [Idea Name] — [one-liner]
   why now: [1 sentence]
   path: [...]

3. [Idea Name] — [one-liner]
   why now: [1 sentence]
   path: [...]

Keep under 3000 chars.

9b. Offer a "build next?" follow-up (force-reply)

If at least one idea was surfaced under "Build This Week", offer the operator a one-tap way to pick which to build — as a separate ./notify after the digest (a digest and a force-reply prompt can't share one Telegram message). Skip the offer entirely on a run that surfaced no picks.

Dedup to once per day: scan the last ~2 days of memory/logs/ for FORCE_REPLY_OFFERED: idea-pipeline::pick; if present, skip this offer. Otherwise send:

bash
./notify "Which of these should I mark as next to build? Reply with the idea's number or name." \
  --force-reply --placeholder "idea # or name" \
  --context "idea-pipeline::pick"

Then record the FORCE_REPLY_OFFERED: idea-pipeline::pick marker in step 10. A pick: reply routes back to this skill and is handled by step 0.

10. Log to memory

Append to memory/logs/${today}.md:

markdown
### idea-pipeline
- **Total ideas:** N_total
- **Screened:** N_screened (by `idea-forge validate`)
- **Executed:** N_executed (skill/prototype/PR match)
- **Gap:** N_gap unexecuted ideas
- **Top pick:** [idea name] — [priority score]
- **Ecosystem feed:** [available / unavailable] — [N underserved categories, M adjacent verticals] (from ecosystem.md, last written [date])
- **Filter:** [var value or "none"]
- **Notification:** sent
- **Force-reply offer:** [offered / skipped — already offered in last 2 days / skipped — no picks]
- FORCE_REPLY_OFFERED: idea-pipeline::pick   ← include this exact line ONLY when the offer was actually sent (it's the once/day dedup marker)
- IDEA_PIPELINE_OK

Required Env Vars

None. Uses local file reads and gh CLI (authenticated via GITHUB_TOKEN in workflow).

Network Note

No external network calls in the main logic. gh pr list uses the gh CLI which handles auth internally (no curl + token pattern needed). WebSearch not required — narrative context comes from memory/topics/market-context.md if present (no shipped skill writes it any more; it is operator-maintained).

© aeonfun, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/idea-pipeline of aeonfun/aeon.

Open the folder on GitHubat commit c0cb7c4

Compare with similar skills

Idea Pipeline next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Idea Pipeline compared with similar skills
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Idea Pipeline this skillaeonfun/aeon767—~3.5kAutomated safety check: PassMIT
Startup Idea Validatormohitagw15856/pm-claude-skills1.4k—~732Automated safety check: PassMIT
Startup Canvasphuryn/pm-skills27k—~1.6kAutomated safety check: PassMIT
Evaluating Startup IdeasRefoundAI/lenny-skills1.4k—~1.7kAutomated safety check: PassMIT
Gapsanthropics/claude-for-legal9.6k2 repos~229Automated safety check: PassApache-2.0
Idea Darwinsickn33/agentic-awesome-skills47k2 repos~1.1kAutomated safety check: PassMIT

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Questions about Idea Pipeline

What does Idea Pipeline do?

Execution-gap audit - cross-references the startup idea backlog against shipped skills, prototypes, and cross-repo PRs, surfacing the top 3 ideas to build next by narrative and operator fit. Idea Pipeline is an agent skill from aeonfun/aeon. Execution-gap audit - cross-references the startup idea backlog against shipped skills, prototypes, and cross-repo PRs, surfacing the top 3 ideas to build next by narrative and operator fit.

How do I install Idea Pipeline in Claude Code?

Run `npx skills add aeonfun/aeon --skill idea-pipeline -a claude-code`. Or copy the skill folder (skills/idea-pipeline in aeonfun/aeon) into .claude/skills/idea-pipeline in your project. Claude Code loads it when a task matches its description.

How do I install Idea Pipeline in Codex?

Run `npx skills add aeonfun/aeon --skill idea-pipeline -a codex`. Or copy the skill folder (skills/idea-pipeline in aeonfun/aeon) into .agents/skills/idea-pipeline in your project. Codex loads it when a task matches its description.

Can I use Idea Pipeline in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add aeonfun/aeon --skill idea-pipeline -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/idea-pipeline, .gemini/skills/idea-pipeline, .github/skills/idea-pipeline and .opencode/skills/idea-pipeline in your project.

What does Idea Pipeline need to run?

Going by SKILL.md and its folder, Idea Pipeline needs the command-line tools its instructions call (gh) and credentials named GITHUB_TOKEN.

Does Idea Pipeline access the network?

SKILL.md names 1 domain. In commands or code: github.com; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.

Is Idea Pipeline safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Idea Pipeline use?

Idea Pipeline is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Idea Pipeline use?

About 3.5k tokens (SKILL.md is roughly 14k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Idea Pipeline?

Skills that share tags, products or a category with Idea Pipeline: Startup Idea Validator (mohitagw15856/pm-claude-skills, 1.4k stars), Startup Canvas (phuryn/pm-skills, 27k stars), Evaluating Startup Ideas (RefoundAI/lenny-skills, 1.4k stars) and Gaps (anthropics/claude-for-legal, 9.6k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Idea Pipeline?

aeonfun (a GitHub organization) maintains it in aeonfun/aeon, which has 767 GitHub stars. The repository holds 82 skills in this directory. The repository was last updated on October 8, 2026.

Source: aeonfun/aeon on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.