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fdeops Reference - one skill, 37 methods across 6 domains

v3 ships one skill: @fde (skills/fde/SKILL.md). You describe the situation; it routes to a phase and follows that phase's method from skills/fde/references/. Engagement memory lives in ~/fde-engagements/<name>/.fde/ (one folder per customer).

Each reference is a method, not advice: the thinking the agent does, the artifact it drafts, and the checkpoint with the human FDE. The Use when column below is what the router actually matches on - the phrases in skills/fde/SKILL.md that send you to that skill, not a paraphrase.


The 6 domains

1. Embed & Trust

First days. Getting access, building credibility, understanding scope.

Skill What it does Use when
land First 48 hours: interrogate the brief, map stakeholders, define success before code Starting fresh, new customer, first meeting, just got the brief
audit Taking over mid-project: verify claims, find the load-bearing wall Taking over, previous consultant left, joining mid-project
stakeholder-radar Map who decides, who blocks, who's about to escalate Need to understand who matters, who decides, who blocks quietly
trust-engineering The trust ladder from observer to trusted; navigate AI policy Need to earn access, navigate AI policy, build credibility
scope-defense "Let me place it": scope receipts, the accumulation conversation "Also can you...", scope expanding, timeline unchanged

2. Discover & Diagnose

Finding the real problem. Testing what the brief claims.

Skill What it does Use when
discover Scan repo + hunt the workaround + workshop facilitation + data estate assessment Don't know the real problem, brief feels wrong, shadow processes
assumption-audit Extract untested assumptions, classify by blast radius, kill the riskiest first The brief feels too neat, assumptions untested, "we just need..."
use-case-scoring Score on value x urgency x alignment x data readiness / complexity Multiple use cases competing, "we want to do everything"
sketch Prototype the killer assumption in one day; kill fast, log the learning Need to validate a direction, prototype, demo to de-risk

3. Plan & Align

Sequencing work and getting sponsor alignment.

Skill What it does Use when
plan Work backwards from success + estimation (3-point sizing) + migration strategy Break this down, what order, sequence the build
business-case Cost of doing nothing -> investment -> return -> sensitivity check Sponsor needs justification, need to defend budget or timeline
options-analysis Three genuine options (conservative / pragmatic / ambitious) Significant decision, multiple approaches, "what should we do?"
initiative-triage 20 things are "urgent"; pick 3 for Now, make trade-offs visible 20 things are "urgent," need to pick the 3 that matter

4. Build & Guard

Safe implementation on someone else's codebase.

Skill What it does Use when
build Blast radius + legacy safety + integration design + team amplification Ready to build, implementing, legacy change, ship a feature end to end
incremental-build Vertical slices, 100-300 lines each, visible progress every 2-3 days Large feature, need visible progress every 2-3 days
test-on-legacy Characterise first, Strangler Fig, spot lying tests No tests, legacy code, need to make changes safely
blast-radius Trace dependencies, classify impact (CONTAINED -> IRREVERSIBLE) What could go wrong, touching shared infrastructure, need to assess impact
debug Systematic: reproduce -> isolate -> one hypothesis -> verify Something's broken, can't reproduce, shouldn't be happening
rescue Production fire, trust fire, wrong-brief-mid-build, or full pivot Production down, urgent - or stakeholder gone quiet, trust slipping
security-audit Threat model in 5 minutes, STRIDE pass, secrets scan Security check, auth/payments/user data, compliance question
observability Define "working" before instrumenting; the four metrics Need monitoring, can't tell when things break, shipping to prod

5. Ship & Verify

Getting to production without surprises.

Skill What it does Use when
ship Intent vs diff (KEEP/JUSTIFY/SPLIT/DROP) + pre-flight + canary + rollback + scale-readiness + progressive adoption Ready to deploy, going live, pre-flight check
review Stage 1 intent vs diff (KEEP/JUSTIFY/SPLIT/DROP), then safety Review this change, is it safe, does it match what we agreed, scope creep in the PR
rollback-drill Test the escape route on staging before you need it at 2am "We can always revert" - need to actually test the escape route
qa-live Test from the user's chair, real browser, five perspectives Need to test from user perspective, "works on my machine"

6. Operate & Close

Running the engagement and ending it well.

Skill What it does Use when
status Sponsor update from the week's actual record Weekly update due, "need to send the sponsor something"
demo-prep The one number, live-vs-canned, five hard questions Demo coming up, show-and-tell, exec walkthrough
debrief Walk out of any meeting -> decisions, signals, actions in memory Just out of a meeting, raw notes, "they said...", "debrief"
exec-narrative Pyramid: governing thought, three supports, SCQA frame Sponsor's boss needs a summary, board update, justify continued investment
dashboard Portfolio view across all customers, trust-ordered Status across all my customers
multi-customer-ops Daily triage, context-switch, cross-contamination prevention Juggling 2+ customers, losing track, context-switching
close Retrospective, the 2am handoff document, what we learned Wrapping up, handoff, making yourself replaceable
handoff-engineering Operations runbook, knowledge transfer, confidence scoring Engagement ending, team needs to operate without you
pattern-extract If you did it twice, encode it; patterns are compound interest Something worked well and will apply to future engagements
red-team Stress-test a plan, handoff, or narrative before someone else does "Red-team this," "stress-test my plan," poke holes, what am I missing
ingest Pull raw text from any source MCP into .inbox/, propose, you confirm "Pull today's transcript," "bring in the Notion page"
ingest-connect Guided config for a source MCP you already trust, plus a reusable recipe "Connect Granola," "wire up Drive"

Overlays (activate on signal, alongside whatever skill is running)

Overlay Triggers on What it adds
ai AI, ML, LLM, model, embeddings, RAG, agents Model selection, RAG architecture, agent safety, governance, drift monitoring, cost management
artifacts deck, slides, report, governance, compliance Executive decks, governance frameworks, ADRs, compliance packs, value reports
fintech payments, PCI, banking, cardholder data Idempotency, transaction integrity, fraud signals, silent-failure prevention
healthcare PHI, HIPAA, patient data De-identification, minimum-necessary, audit trails
gov FedRAMP, ATO, CUI, classified Authority boundaries, CUI marking, continuous monitoring

AI companion (not a sixth overlay): eval-pack - golden set / pass-fail before AI ship (evals.md). Loaded with the ai overlay when models are in scope.


Engagement phases (quick reference)

The 10 phases most engagements actually run through, with what gets written where. This is a shorter cut through the table above - see it for the full 35.

Phase Enter when Method highlights Writes
land New customer, first meeting Interrogates the brief for what's missing; coaches the sponsor conversation; maps stakeholders and sacred data brief.md success.md stakeholders.md trust-profile.md
discover Brief feels wrong, real problem unclear Runs churn/test-gap/"temporary"-archaeology/AI-component scans; hunts the workaround; scores use cases reality.md terrain.md
audit Taking over half-done work Reads everything, tests every "this works" claim, finds tribal-knowledge holes via git authorship audit.md terrain.md reality.md context.md
sketch Direction needs validating Prototypes the killer assumption same-day; kill criteria; 3-sentence business case prototype-log.md business-case.md
rescue Production fire, trust fire, or wrong-brief mid-build Stabilise -> named unknowns -> minimum safe change; quiet-stakeholder protocol; three-path reset chaos-log.md risks.md decisions.md
close Engagement ending Retrospective with receipts; pattern extraction; the 2am handoff retrospectives/ patterns.md handoff.md
plan Scope clear, needs sequencing Backwards from success; fragile first; PR-sized tasks; acceptance-criteria gate decisions.md
build Agreed slice ready Blast radius declared; characterisation tests on legacy; Strangler Fig; cleanup pass decisions.md risks.md delivery.md
review Change needs a merge gate Stage 1 KEEP/JUSTIFY/SPLIT/DROP vs stated intent, then 5-dimension safety; review-fix loop until clean decisions.md
ship Ready to deploy Intent vs diff receipt, then pre-flight/CAB; canary with rollback-on-anomaly; pulse before closing the laptop delivery.md

The fde CLI (deterministic core - works without AI)

scan recon + "ASK ON DAY 1" questions (zero-config via npx fdeops scan) · resume [--full] [--init <name>] memory (bounded by default - current state + recent activity; --full for the complete log) + the one canonical setup step (--init creates AND binds the workspace) · debrief <file> (or stdin) route decision:/risk:/delivery:/contact: prefixed lines to their .fde files with dates, everything else to a dated block in context.md · log <type> <text> [--signal green|amber|red] structured appends; --signal writes the [signal:...] token that drives trust in status/dashboard (stale after 21 days) · receipts <term> agreements with dates · capture session snapshot · status portfolio triage · dashboard [--open] [--out <path>] render every engagement into one offline fieldbook.html. The skill calls these for mechanics; the AI does interpretation and judgment. Every command above runs locally - no AI needed.


The memory contract (what makes it a second brain)

  1. On entry the agent reads a bounded view of context.md (via fde resume) - nothing else until the phase needs it.
  2. Deliverable = memory: every phase's output IS a .fde/ file; nothing is maintained by hand.
  3. Every claim carries evidence: (ops lead, Day 5) · (churn: 47/90d) · (stated, unverified).
  4. On exit (and before a PR) the agent runs a session digest — TL;DR, key decisions & why, scope/verification, gotchas, next action — into existing .fde/ files (not chat transcripts into the product repo); the session-stop hook backstops a thin snapshot (hooks resolve the engagement via the workspace registry written by fde resume --init).
  5. One customer, one folder. Never merged.

v2's 16 standalone skills were consolidated into the single @fde router in v3.