Research

Business Research

Collect the data behind a business-value claim for an AI skill or agentic workflow — productivity, time saved, quality, capacity, delivery outcomes — into the interim run package the report commands render from. Value is stated in engineer-hours, cycle time, throughput, quality, and capacity. Never money.

Read these first; they bind every step:

• ../../references/interim-format.md — the run package layout and where runs live.
• ../../references/provenance.md — the four tags, the anti-inflation rules, and the no-currency contract.
• ../../references/measurement.md — what the data must feed: the saving formulas, statistics discipline, the counterfactual ladder, and the quality guardrails.
• ../../references/instruments.md — per-instrument probes, collection discipline (timezone and cohort conventions, the GraphQL filteredCount trap, absence snapshots), and the collection targets in query-ready form.

User arguments: $ARGUMENTS

Context

Today: !date +%F

Kernel (WSL detection): !grep -qi microsoft /proc/version 2>/dev/null && echo "WSL" || echo "(not WSL)"

Instruments on PATH: !for c in git gh jq; do command -v $c >/dev/null && echo "$c: available" || echo "$c: unavailable"; done

gh: !gh auth status 2>&1 | head -3

Procedure

1. Scope and orchestration plan

Present an orchestration plan before touching disk: what will be measured, over what pinned date range, with which instruments, to which output directory. Enter plan mode if the host supports it — Claude Code EnterPlanMode; Cursor, Codex, or Gemini via /plan or Shift+Tab; otherwise present the plan as plain text and pause. Ask where to write the run, defaulting per the location rules in interim-format.md (Documents root; on WSL prefer the Windows Documents folder when detected). Wait for confirmation.

2. Instrument discovery — never assumption

Probe what is actually available using the per-instrument probes in instruments.md; never assume an instrument exists. Candidates (illustrative, not a fixed list): git history; gh (verify auth and rate limits before relying on it); ticket-tracker MCPs or CLIs such as Jira or Linear; CI telemetry; session logs; time-tracking exports. Record every instrument as available or unavailable in the run README. Data an unavailable instrument would have provided is recorded as unknown — never fabricated, never silently skipped.

3. Collect

For each available instrument, run pinned-window queries per the collection discipline in instruments.md and snapshot raw output into raw/ before deriving anything. Targets — collect what the instruments support and record the rest as unknown:

• Task and PR cycle times, review latency. Prefer GraphQL over the Search API for reliability; paginate; compute distributions client-side.
• Rework signals: reverts, reopened items, CI failure and retry rates, PR-size drift.
• Per-task timing where measurable: manual baseline vs AI-assisted duration, including verification/review time and failed-run time.
• Adoption signals: distinct users of the skill vs the eligible population — record license-holding and active use as separate numbers.
• Skill build and maintenance time: reconstructed from history if possible, else ESTIMATED with rationale.

4. Write the package

Emit the full interim format from interim-format.md: run README, source manifest with verbatim queries, assumptions register, raw snapshots, per-topic measurements, and findings.md. Every figure tagged; every unknown listed with what data would resolve it.

Rules

• Raw snapshots are immutable once written.
• An unavailable instrument yields unknown, not an estimate — unless the user supplies an assumption, which is registered as ESTIMATED with rationale and owner.
• No currency in any output, per provenance.md.

Output

Open with a one-line hero (✓ Run written: <run path>, window <start>..<end> or ⚠ Halted: <reason>), then exactly these sections:

1. ## Scope — what was measured and the pinned window.
2. ## Instruments — available vs unavailable, and what each unavailable one leaves unknown.
3. ## Collected — per instrument: what landed in raw/ and measurements/.
4. ## Package — the run path, count of registered assumptions, and the open unknowns.

End with an AskUserQuestion panel: generate a report (ask which tier), collect more, or stop. Skip the panel in plan mode or when running non-interactively.