oracle
Skill2 starsChanged 53 days agoMITView on GitHub
Daily idea engine. Scans the last 7 days of your connected systems and your internet-reader sources, scores candidate "content spikes" against the shared rubric, appends everything to your Spike Vault, and returns a ranked list of 10-15. Trigger phrases include "run the oracle", "find content spikes", "/oracle".
55 other projects use a version of this.
Adopted by
Most recently taken up by
- valentinesamuel/claude-skillstheir own version, first seen Nov 8, 2026
- insight68/Skillstheir own version, first seen Nov 8, 2026
- antoniolg/agent-kittheir own version, first seen Nov 8, 2026
- incognitojam/skillstheir own version, first seen Nov 7, 2026
- QVerisAI/QVerisBottheir own version, first seen Nov 1, 2026
- agentmemoir/skillstheir own version, first seen Nov 1, 2026
Used with
Projects with it also use taskflow-inbox-triage, BlueBubbles and 10 more.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
AtomicBot-aiSkilltaskflow-inbox-triage
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为Clawdbot构建或更新BlueBubbles外部通道插件(扩展包,REST发送/探测,webhook入站)。
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seedprodSkillvoice-call
Start voice calls via the OpenClaw voice-call plugin.
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hkyutongSkillopenclaw-release-maintainer
Maintainer workflow for OpenClaw releases, prereleases, changelog release notes, and publish validation. Use when Codex needs to prepare or verify stable or beta release steps, align version naming, assemble release notes, check release auth requirements, or validate publish-time commands and artifacts.
Also in 4 projects that use this
seedprodSkillsession-logs
Search and analyze your own session logs (older/parent conversations) using jq.
Also in 15 projects that use this
AtomicBot-aiSkilltaskflow
Also in 6 projects that use this
- +5 more from seedprod
Other versions55 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 55
- moltbot/clawdbot★ 394ksame name
- steipete/warelay★ 394ksame name
- steipete/clawdis★ 394ksame name
- moltbot/moltbot★ 394ksame name
- clawdbot/clawdbot★ 394ksame name
- openclaw/openclaw★ 394ksame name
- molt-bot/clawdbot★ 391ksame name
- spinabot/brigade★ 11ksame name
- steipete/agent-scripts★ 7.4ksame name
- the-open-agent/openagent★ 5.7ksame name
45 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository6 other files it gives its agents.
- content-machineSkill
- content-setupSkill
- draftSkill
- interviewSkill
- lessonsSkill
- repurposeSkill
The file
We split this skill into the rules it gives an agent
2 rules. 0 are common, 1 is distinctive, and 1 is very specific to this project.
0
Common
Most of the 54 edited versions we read keep these.
1
Distinctive
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 10
Read first: reference/spike-scoring.md (the scoring contract) and the personal folder's sources.md (what you may scan).
- Distinctive: line 26
Use whatever connected tools the environment provides (MCP servers, web fetch/search).
“Common” is measured: kept by at least 6 in 10 of the 54 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Oracle — mine the week for content spikes
Read first: reference/spike-scoring.md (the scoring contract) and the personal folder's sources.md (what you may scan). Personal folder resolution: ~/.content-machine/redirect.md first line if present, else ~/.content-machine/.
Hard rules
- Scan only sources listed in
sources.md. Systems it marks off-limits are off-limits even if credentials are available. Ifsources.mdnames a screening rule for a source (e.g., an employer-confidentiality boundary), apply it to every spike from that source before listing it. - Window: last 7 days. Older material only if
sources.mdsays otherwise. - Score every candidate with the rubric. ≥ 6 makes the list; everything scored goes to the Spike Vault (
spike-vault.mdin the personal folder) with date, score, source, and one-line statement — used or not. Ideas are inventory. - Target 10–15 list entries, roughly half internal / half internet reader. Fewer is fine; padding with sub-6 spikes is not.
- Also surface repurpose candidates: scan the personal
drafts/folder for published pieces whose spike is alive again (a debate reignited, a number updated). Mark theseREPURPOSE.
Scan procedure
Internal (per sources.md): notes/vault folders, meeting notes, journals, email, chat workspaces, task/issue trackers, calendar. You're hunting moments: a story told in a thread, a strong claim made on a call, a number that surprised someone, a customer sentence worth quoting.
Internet reader (per sources.md): the listed accounts and sites, last 7 days. You're hunting live debates and posts worth responding to. Every internet spike names its response mode: quote-post, reply, or standalone.
Use whatever connected tools the environment provides (MCP servers, web fetch/search). If a listed source has no available tool, say so in the output — don't silently skip it.
Output
The ranked list in the exact format from reference/spike-scoring.md, internal and internet sections labeled, repurpose candidates at the end. Then one closing line: which spike you'd pick and why — one sentence, no hedging.
❌ Bad output entry: "You had some interesting discussions about AI this week that could make good content."
✅ Good output entry: [9] SLACK #client-calls — Banker rebuilt McKinsey's 6-month proposal in one week with Claude Code; consulting is repricing in real time. why it scores: lived story + numbers + live debate.
After the run
Confirm the Spike Vault append happened (count entries before/after). The user picks a spike and continues with /interview.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

