Digital-Workforce
CLAUDE.md1 starsChanged 4 months agoMITView on GitHub
This repo is a runnable implementation of Nufar Gaspar's lecture "Executive AI Readiness Framework — Archetypes, Operating Principles, and Digital Employees." It gives an executive a team of AI "digital employees" they operate as Claude Code skills. Every employee reads from the user's Personal Context System (context/) so its output sounds like them, not a generic executive. User-facing overview: README.md. Internal authoring spec: .claude/BUILD_SPEC.md. Canonical text: .claude/OPERATING_PRINCIPLES.md. In short: 1. Speak, don't type — invite dictation; never penalize messy, out-loud…
In this repository12 other files it gives its agents.
- brain-dumpSkill
- chief-of-staffSkill
- comms-expertSkill
- docx-reviewSkill
- handoffSkill
- interview-meSkill
- onboardSkill
- ops-powerhouseSkill
- research-analystSkill
- sort-knowledgeSkill
- strategic-advisorSkill
- wiki-lintSkill
The file
We split this CLAUDE.md into the rules it gives an agent
2 rules. About 0 are common, 1 is distinctive, and 1 is very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈1
Distinctive · estimate
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 53
Use AskUserQuestion for structured choices (2–4 real options).
- Distinctive: line 143
Every action item needs an OWNER and a DELIVERY DATE: No action, commitment, or next-step is recorded — in any deliverable (briefs, decks, …
≈ “Common” is an estimate: at least 1 in 5 of the 26,980 CLAUDE.md 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
CLAUDE.md — Digital Workforce project memory
This repo is a runnable implementation of Nufar Gaspar's lecture "Executive AI
Readiness Framework — Archetypes, Operating Principles, and Digital Employees."
It gives an executive a team of AI "digital employees" they operate as Claude
Code skills. Every employee reads from the user's Personal Context System
(context/) so its output sounds like them, not a generic executive.
User-facing overview: README.md. Internal authoring spec: .claude/BUILD_SPEC.md.
The 5 Operating Principles (non-negotiable — apply to everything)
Canonical text: .claude/OPERATING_PRINCIPLES.md. In short:
- Speak, don't type — invite dictation; never penalize messy, out-loud input.
- Brain-dump habitually — capture undocumented context with low friction.
- Have AI interview you — surface blind spots before producing output.
- Separate planning from execution — plan the approach, get approval, then execute. Use plan mode for judgment-heavy work.
- Be intentional about the intervention point — capture the user's primer / initial thoughts up front; flag the moments their judgment matters most. Always engage their judgment at the start.
THE LIVING WIKI + the Wiki Contract (how the system compounds)
context/ is treated as a living, interlinked wiki (Karpathy's "LLM Wiki"
pattern), not a static folder. Knowledge is synthesized at ingest time so it
accumulates. Three layers: raw/ (immutable sources) → context/ (the
synthesized, [[linked]] wiki, with index.md catalog + log.md ledger) → the
schema docs. Full spec: .claude/WIKI.md.
Every skill, agent, and task follows the Wiki Contract:
- Orient — read
context/index.md, open the linked pages you need first. - Do the work.
- Write back — synthesize durable knowledge into the right page (don't dump
raw text), add
[[links]], cite provenance (raw/...), flag contradictions instead of silently overwriting, and updatecontext/index.md. - Log it — append a timestamped line to
context/log.md(get the time fromdate "+%F %H:%M").
Operations: Ingest (/sort-knowledge, /brain-dump), Query (every
employee — and they file insight back), Lint (/wiki-lint).
THE GOLDEN RULE (overriding instruction)
Wherever the lecturer says the executive should provide input, the skill must actively interview the user for it — never assume, never ask for a blob.
Concretely, in every skill and any task here:
- Load
context/first, summarize what's already known, and only ask for what's missing or stale. - Use
AskUserQuestionfor structured choices (2–4 real options); use plain conversational questions for open-ended elicitation, one focused question at a time — keep going until blind spots are covered. - Persist anything reusable back into
context/and tell the user, on screen, what you saved and where. They should never have to repeat it. - Capture the user's primer (existing assumptions/opinions) before doing work.
Portability rule
This repo is shared open source. Never hardcode absolute machine paths (no
/Users/...). Always use paths relative to the repo root (e.g.
context/profile.md, .claude/agents/board-advisor.md, outputs/research/).
The user's real context/ and inbox/ data is git-ignored; only *.example.md,
READMEs, and structure are committed.
The map
Skills (.claude/skills/<name>/SKILL.md):
/onboard— builds the context system (profile, company, decision-style). Run first./interview-me— pre-task grilling → primer → routes to the right employee./brain-dump— low-friction capture of undocumented context./research-analyst— decision-driven research, wisdom-of-crowd fan-out, fact-check./strategic-advisor— board of advisors debate a decision in the user's style./comms-expert— writes in the user's voice, reviewed through reader personas./ops-powerhouse— briefs, P&L reads, meeting prep, multi-channel synthesis./chief-of-staff— capstone: orchestrates the four employees into one deliverable./sort-knowledge— bulk-ingestsinbox/into thecontext/wiki via the librarian (synthesize → link → flag contradictions → archive toraw/→ log)./wiki-lint— wiki health check: contradictions, stale claims, orphans, missing links, gaps./handoff— compact the current session's volatile state into a handoff doc in the OS temp dir (references the wiki/artifacts, never duplicates them) so a fresh agent resumes cleanly. Takes the next session's focus as an argument./docx-review— review/mark up a Word.docxwith real comments, threaded replies, and tracked changes viaintegrations/docx/docx_comments.py(stamps the REAL timestamp, not midnight; registers the author so replies thread; emits a markdown mirror). Use for any "review/comment on/redline this doc".
Subagents (.claude/agents/): research-scout, fact-checker (→ research-analyst);
board-advisor (→ strategic-advisor); reader-persona (→ comms-expert);
knowledge-librarian (→ sort-knowledge); wiki-lint (→ wiki-lint).
Model policy (.claude/MODELS.md): which model tier does which work —
escalate where judgment concentrates (fact-check, high-stakes board debates →
strongest available, fable → opus → inherit), downgrade where breadth
concentrates (scouts sonnet, reader personas haiku, librarian/lint
sonnet). Rolling aliases only — never dated model IDs. Follow it whenever
spawning agents, even outside a named skill.
Workflows (.claude/workflows/): multi-model-research.ts,
chief-of-staff-briefing.ts. The automatable end-state of the research and
chief-of-staff skills. See .claude/workflows/README.md. Runtime forbids the
clock and randomness — pass timestamps via args.
Context wiki (context/ — the living knowledge base): control files
index.md (catalog) + log.md (ledger); concept pages profile.md,
company.md, decision-style.md, writing-style.md; and the folders
decisions/, stakeholders/ (personal CRM), writing-samples/, advisors/,
reader-personas/, brain-dumps/, reference/. See context/README.md and
.claude/WIKI.md.
Raw source library (raw/ — immutable): originals of ingested material;
provenance for wiki claims. Drop new material in inbox/; /sort-knowledge
archives originals to raw/.
Lint (/wiki-lint + .claude/agents/wiki-lint.md): wiki health check —
contradictions, stale claims, orphans, missing links, gaps. Run weekly.
Hooks (.claude/settings.json): SessionStart reports context status / nudges
/onboard (the one shipped hook — lightweight, non-blocking).
Output style (.claude/output-styles/executive.md): terse, decision-first.
Knowledge inbox (inbox/): drop zone for bulk docs; processed by
/sort-knowledge into context/, originals archived to raw/.
Integrations — the capability catalog (integrations/README.md): READ THIS before
assuming a capability doesn't exist. Built tooling lives under integrations/:
docx (Word comments/redlines + markdown-diagram rendering), drawio (editable
diagrams), gemini (image generation), transcription (audio → text),
video (video ingest + OCR). When you build a new integration, add it to
integrations/README.md AND here, so the next session discovers it.
Default behavior for Claude in this repo
- Follow the Wiki Contract (orient → work → write back → log) on every task, even outside a named skill. The wiki is how the system compounds.
- Interview, don't assume. Apply the Golden Rule on every task that has
user-specific inputs, even outside a named skill. Pull from
context/first. - Encourage dictation. Remind the user they can speak long answers; accept messy input gladly.
- Separate planning from execution. For judgment-heavy or critical work, plan the approach and surface it for approval (plan mode) before producing the deliverable. Don't jump to output when there's thinking to be done.
- Capture primers up front and flag where the user's judgment adds the most value — design the rest to run without them.
- Persist learnings to
context/and say what you saved and where. - Every action item needs an OWNER and a DELIVERY DATE. No action, commitment,
or next-step is recorded — in any deliverable (briefs, decks, status, proposals) —
without a named owner and a concrete date (not "TBD"/"soon"). If a date isn't
committed yet, supply a best-estimate marked
EST; if the owner is truly undecided, flag ⚠️ and ask the user. - Deliverables go to
outputs/(research/,briefs/,comms/), organized by subject area (artifacts and their generating scripts kept together). Deliverable content is private by default — only structure (.gitkeep,*.example.md) is ever committed. - Match the tone: concrete, opinionated, warm, anti-generic. Each employee should feel like a specific person, never a faceless assistant.
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.

