naming-the-machine
Skill1 starsChanged 5 months agoMITView on GitHub
Scan skills, tools, workflows, and infrastructure to identify and name emergent expressions of value — products, methodologies, brands, or IP assets hidden in existing systems. Triggers on "what have I built," "find products in my systems," "audit for marketable expressions," or "name everything.
We split this skill into the rules it gives an agent
5 rules. About 0 are common, 5 are distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈5
Distinctive · estimate
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 12
Default: full audit. Unrecognized scopes fall back to full audit.
- Distinctive: line 26
Start from what exists, skip what doesn't, never error on missing paths.
- Distinctive: line 34
Use subagents for parallel scanning.
- Distinctive: line 36
Cross-scope stitching: After scanning individual layers, look for patterns that span layers (e.g., a cron -> agent -> skill chain).
- Distinctive: line 46
If it involves client work, annotate "verify IP ownership" but don't disqualify.
≈ “Common” is an estimate: at least 1 in 5 of the 308,232 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Naming the Machine
Invocation
naming-the-machine [infrastructure|projects|workflows]
Default: full audit. Unrecognized scopes fall back to full audit.
Signal Levels
| Level | Definition | Test |
| Named | Functioning system, unlabeled. 3+ active components producing output today | Could you demo it right now? |
| Emergent | Repeating pattern producing value across multiple sessions or projects | Would you notice if it disappeared? |
| Nascent | 1-2 components exist, others hypothetical | Can you describe the missing piece? |
Execution
Scan
Start from what exists, skip what doesn't, never error on missing paths.
Sources (check all that exist; scope narrows which to prioritize):
- Always: CLAUDE.md, skills index, context files, memory files
- Projects: Git repos or dirs with
CLAUDE.md/package.json-- prefer diversity over recency, cap at 20, read READMEs/architecture docs only - Infrastructure: Cron jobs (
crontab -l), systemd services, MCP configs, tool registries - Workflows: Slash command tables, agent dispatch patterns, session save/load patterns
Use subagents for parallel scanning. Read structure first; drill into files only when they show signals. First run: scan broadly. Subsequent runs: focus on changes since last run.
Cross-scope stitching: After scanning individual layers, look for patterns that span layers (e.g., a cron -> agent -> skill chain). Composite patterns are often the most valuable and least visible.
Disqualify
A pattern must pass all three gates:
- 3+ distinct components — single tools or configs don't qualify; aliases for the same thing don't count as separate components
- Repeating — used across multiple sessions, projects, or time periods (within-session recurrence alone is insufficient)
- Referenced or reused — the user has invoked, described, or built on this pattern (not just theoretically valuable)
If it involves client work, annotate "verify IP ownership" but don't disqualify.
Name
For each surviving pattern:
## [Working Title]
**Signal:** named | emergent | nascent
**Value lever:** One sentence — what outcome does this arrangement produce?
**Next action:** Ship it / name it publicly / add [specific missing piece] / watch itFor named items, add: Linchpin — the one component that, if pulled, the whole arrangement falls apart.
Naming guidelines: Name the value, not the mechanism. Two words preferred, three max. It should make someone ask "what's that?"
Summary Matrix
| # | Working Title | Signal | Value Lever | Next Action |
|---|--------------|--------|-------------|-------------|Sort: named → emergent → nascent.
Persist and Diff
Save to <your-output-dir>/naming-YYYY-MM-DD.md. On first run, just save.
On subsequent runs, find the most recent prior file and diff:
- New — not in prior run
- Promoted — signal level increased
- Retired — in prior run, no longer present
Include delta in output.
Output
NAMING COMPLETE: [count] expressions identified
named=[n] emergent=[n] nascent=[n]
DELTA: [n] new, [n] promoted, [n] retired (omit on first run)In this repository54 other files it gives its agents.
- AGENTS.mdAGENTS.md
- skills/deep-recon/agents.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
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- data-analyst-agentSkill
- database-migrationsSkill
- deep-reconSkill
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- doc-coauthoringSkill
- e2b-sandboxSkill
- ecosystem-auditSkill
- excalidraw-diagramSkill
- executing-plansSkill
- frontend-designSkill
- fullstack-agentSkill
- grillSkill
- kickoffSkill
- mcp-builderSkill
- model-migrationSkill
- full-output-enforcementSkill
- package-researchSkill
- pdf-generationSkill
- pp2pSkill
- pp3pSkill
- prompt-engineerSkill
- prompt-groundingSkill
- redesignSkill
- requesting-code-reviewSkill
- reverse-engineer-to-learnSkill
- review-changesSkill
- scratchpadSkill
- shipSkill
- slack-gif-creatorSkill
- sprint-architectSkill
- techdebtSkill
- test-and-fixSkill
- threat-modelSkill
- verification-before-completionSkill
- visual-verdictSkill
- webapp-testingSkill
- web-asset-generatorSkill
- whatdidimissSkill
- writing-plansSkill
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.

