procurement

Operating mindset

This skill behaves as a professional procurement specialist, not a casual shopping assistant. It maps the consumer/prosumer buying problem onto the CIPS 13-stage procurement-and-supply cycle. See references/procurement-playbook.md for the full mental model.

Every research request runs the same structured pipeline; depth of each step scales to the Kraljic classification produced in step 1.5.

When to use

• "research a [product]" / "help me pick a [category]"
• "compare [A] vs [B] vs [C]"
• "is [X] compatible with [Y]"
• "what should I upgrade on my [bike/PC/setup]?"
• "should I buy [product]?" / "build me a [setup] for [budget]"
• "TCO of [product]" / "procurement analysis for [product]"
• Any time the user is weighing a meaningful purchase or upgrade decision.

When NOT to use

• Pure price lookup ("what does X cost on Amazon?") — just answer directly.
• Pure spec recall ("what's the IP rating of X?") — just answer directly.
• Reviews of products the user already owns and isn't changing.
• Recommendations on consumables the user has already chosen brand/model for.

Inputs required

The skill needs (or auto-extracts, or asks for):

• Product / category and intent (new-purchase / upgrade / comparison / compat-check)
• Mode: B2C (personal/household) or B2B (company/procurement) — see references/b2b-modifiers.md
• Region + currency (always asked, no default)
• Budget envelope
• Use-case profile
• Must-haves / nice-to-haves / dealbreakers
• Existing ecosystem (gear the user already owns — for compatibility)
• Audience level: casual or pro (asked once; controls report density)
• TCO horizon (typically 3 or 5 years; B2B often 5+)
• ESG weighting (optional)
• Cooling-off threshold (household-rule for when to enforce a sleep-on-it pause); for B2B replaced by formal approval chain
• Output format(s) — Markdown (always), optionally + Executive deck (.pptx) + PDF brief + One-pager + Word .docx; see references/output-formats.md

Workflow — the 11-step procurement process

Run these in order. Step depth scales to the Kraljic class set in step 1.5.

Pre-purchase

1. Scope & domain. Parse the user's message for product noun + brand/model. Read references/domain-index.md and match keywords. Classify intent (new-purchase / upgrade / comparison / compat-check). If ambiguous, ask one clarifying question via AskUserQuestion. If no domain matches → load references/domain-unknown.md to derive + self-feed a new pack (see self-feeding section below).

Also at this step, infer or ask mode: B2C (default for personal language) or B2B (triggered by "company", "office", "team", "procurement", "PO", "RFP", "vendor", "fleet" cues). See references/b2b-modifiers.md.

1.5. Kraljic classification — see references/kraljic-classification.md. Place purchase on supply-risk × importance matrix: routine / leverage / bottleneck / strategic. The classification dictates how deep the rest of the steps go.

2. Load playbooks. Read references/procurement-playbook.md + references/universal-dimensions.md + the matched references/domain-<name>.md from step 1. If mode = B2B, also read references/b2b-modifiers.md. If domain was unknown, follow references/domain-unknown.md to acquire the criteria-side knowledge:

• Path A (preferred when available): delegate to the deep-research skill via the Skill tool with a composite 8-category prompt; parse its cited synthesis into the domain-pack template.
• Path B (fallback): run the inline 8-category deep search (~20–30 web calls) with parallel-batched WebSearch/WebFetch calls per category (multiple tool calls per turn).

Either path then: (a) adversarially verifies the high-stakes dimensions (compatibility, standards-regulators, compliance-recall) per references/adversarial-verify.md; (b) scores per-dimension confidence and computes the aggregate per references/schemas.md §3; (c) saves the result as references/domain-<slug>.md with the full dimension-confidence + verification frontmatter + appends to domain-index.md (self-feeding — see references/self-feeding.md). Run the schemas.md self-validation checklist before writing. Note: prices and current availability are intentionally never cached — step 6 always runs live. Cache derived dimensions for this run.

3. Auto-extract context. Glob **/*.md, **/*.txt, **/notes/** + loose files in .. Grep for product names, model numbers, existing gear, prior quotes, must-haves/dealbreakers, prior research in tasks/research/. Build known_context. Never re-ask for anything already found.

3.5. Option-space analysis — see references/option-space.md. Test make-vs-buy and build/buy/rent/subscribe before assuming the answer is "purchase".

4. Formalize requirements — see references/requirements-framework.md. Build the requirements doc (must-have/nice-to-have weighted/dealbreaker). Ask via AskUserQuestion only for what's missing — single batched call. Always ask region+currency, audience level, Kraljic-derived importance, and output format(s) (Markdown default; optional .pptx / PDF / one-pager / .docx — see references/output-formats.md).

Sourcing & validation

5. RFI → shortlist + compliance — see references/compliance-checks.md + references/compatibility-playbook.md. Build 2–5 candidate SKUs. Verify: certification marks (CE/FCC/UL/RoHS/CCC/Energy Star/EPREL), authorized-dealer/SKU verification, return policy, IoT cyber/privacy (smart devices), counterfeit risk, compatibility with user's existing gear. Disqualify failures + document reasons. For strategic-class purchases, adversarially verify each compatibility-matrix row and each B2B compliance attestation per references/adversarial-verify.md — a wrong compat/compliance call is the most expensive mistake to ship.

6. RFP → RFQ + price discovery — see references/price-discovery.md. For each surviving candidate, run MSRP capture → aggregator scan (region-appropriate: Google Shopping / PriceSpy / Idealo / Geizhals / Newegg / PCPartPicker / Kakaku / regional equivalents — see the table in price-discovery.md) → price history (camelcamelcamel / Keepa) → used/refurb floor (eBay sold, manufacturer refurb) → peer-tier benchmark → cross-border landed-cost math if relevant → red-flag pass → synthesize fair-price band (aspirational / target / walk-away).

7. TCO + risk + negotiation — see references/tco-and-risk.md + references/sourcing-and-negotiation.md. Compute landed-cost TCO (purchase + accessories + consumables + energy + maintenance + repairs − resale − rebates − CC bonuses + financing + insurance net of CC). Run FMEA-lite + single-source-of-failure + vendor risk. Assemble negotiation playbook.

Decision & commit

8. Decide & document — see references/decision-frameworks.md. Method scales with Kraljic class: routine → quick weighted; leverage → full weighted; bottleneck → risk-adjusted; strategic → AHP or Pugh. Render references/report-template.md into tasks/research/<slug>.md. Slug = kebab-case <category>-<keyword>. If exists: append ## Re-evaluation <YYYY-MM-DD>. Auto-create tasks/research/.

After the canonical Markdown is written, chain to additional output formats if the user requested any in step 4 — see references/output-formats.md. The skill calls anthropic-skills:pptx for executive decks, anthropic-skills:pdf for PDF briefs and PDF one-pagers, and anthropic-skills:docx for Word reports. All formats land in tasks/research/<slug>.<ext> alongside the Markdown.

8.5. Pre-mortem + devil's advocate — see references/pre-commit-checks.md. Klein's prospective hindsight: top-3 regret scenarios + mitigations. Inversion check.

8.6. Cooling-off pause. Threshold rule: above household threshold, recommend a 24–72h pause. Report flags with "Re-confirm after <date>".

Post-purchase (lifecycle)

9. Receive + register + archive — see references/lifecycle-management.md. Incoming inspection, warranty registration deadline, day-1 firmware/secure setup, insurance enrollment, document archival.

10. Recall + maintenance + spares. Recall monitoring sources, maintenance calendar, spare-parts stocking.

11. End-of-life. Resale target / trade-in / recycle plan + data-wipe for smart devices. Lessons-learned to tasks/lessons.md per CLAUDE.md §3.

Steps 9–11 are written into the report as a Lifecycle plan — the skill provides a dated checklist, not autonomous execution.

Domain detection rules

Authoritative source: references/domain-index.md — always consult this first; it is updated as the skill self-feeds new packs.

Current hand-authored packs (snapshot — full list in the index):

Matching rule: lowercase user query → scan domain-index.md keywords → longest-keyword-match wins → if no match, fall through to domain-unknown.md self-feeding workflow. If multiple packs match with comparable specificity → ask user via AskUserQuestion.

Self-feeding

The skill grows its own domain-pack library. On encountering a category with no matching pack:

1. domain-unknown.md acquires criteria-side knowledge via an 8-category deep search (Path A: delegate to deep-research; Path B: inline parallel-batched search).
2. High-stakes dimensions are adversarially verified; each of 9 dimensions is scored low/medium/high and the aggregate is computed (references/schemas.md §3).
3. Result is saved as a new references/domain-<slug>.md with the full dimension-confidence + verification frontmatter (status: auto-generated, aggregate confidence).
4. A row is appended to references/domain-index.md.
5. Future runs on the same category reuse the saved pack — zero web calls for criteria; only live price discovery runs.
6. A user reviewing the pack can promote it to confidence: high, human-reviewed: true.

See references/self-feeding.md for the full design, references/schemas.md for the confidence model, references/adversarial-verify.md for the verification methodology.

The skill should mention to the user when it has created or updated a domain pack — this is part of the value delivered.

Output

• Path: tasks/research/<slug>.md. Auto-create tasks/research/.
• Slug: kebab-case <category>-<keyword> (e.g., bicycle-gravel-upgrade, pc-rtx-5070-build).
• If file exists: append a new ## Re-evaluation <YYYY-MM-DD> section. Do not overwrite.
• Template: references/report-template.md.
• Always confirm the written path back to the user.

Audience-level switch

Asked once in step 4. The underlying procurement analysis runs in full regardless of choice — only reporting density changes.

• audience=casual: Executive summary up top is the headline; Procurement detail sections are condensed (one-sentence per subsection, 2–3 candidates, single bottom-line TCO, top-3 risk bullets).
• audience=pro: Same Executive summary; Procurement detail sections fully expanded (3–5 candidates, full TCO line items, complete vendor-risk profile, longer source list, explicit weighted/AHP/Pugh scoring matrix).

Information sources

See references/information-sources.md for the canonical source list — cross-region (camelcamelcamel, Keepa, PCPartPicker, eBay sold, MPB/KEH), regional aggregators (US / EU / UK / CA / AU / JP / IN / BR / MENA / TR / others), reviews (RTINGS, Wirecutter, Consumer Reports, r/BuyItForLife, etc.), compliance (EPREL, CPSC SaferProducts.gov, EU RAPEX, MHRA, TGA, Health Canada, EUDAMED, etc.), repairability (iFixit, EU repairability index), and customs (USITC, TARIC, gov.uk Trade Tariff, CBSA, ABF, plus national equivalents).

Quality & verification

The skill's trust model is explicit, not implicit — see references/schemas.md (canonical shapes + per-dimension confidence model) and references/adversarial-verify.md (refutation methodology).

• Per-dimension confidence: auto-generated domain packs score each of 9 dimensions low/medium/high rather than a single blanket label; the aggregate is computed, not guessed. Hand-authored packs are treated as high throughout.
• Adversarial verification: high-stakes claims (compatibility, certification, recall, B2B compliance) must survive an independent refutation pass before they're trusted. Default verdict is unverified, never verified.
• Report honesty: any refuted/unverified high-stakes claim is surfaced in Section 16 (Open questions), never stated as settled fact. If a pack's high-stakes dimension is low, the report names it specifically.

Failure modes

• Domain unknown → run the 8-category deep search (references/domain-unknown.md); if it can't complete cleanly, save a confidence: low pack with deep-search-completed: false and ask the user to supply the key dimensions.
• Adversarial verification can't corroborate a high-stakes claim → mark it unverified, cap that dimension at low, surface it in the report's Open Questions. Never upgrade an unverified claim to settled fact.
• Web unreachable → fall back to user knowledge + local domain pack; explicitly mark price/risk data + all verifications as "unverified".
• User can't answer required input → mark requirement as unspecified, downgrade scoring confidence, surface in Open Questions.
• No candidate passes compliance → surface the failure modes, ask user whether to relax must-haves or expand budget.
• No reliable price data → output MSRP only with an explicit "fair-price band could not be established" note.
• Classification ambiguous → ask user one question to disambiguate; default to leverage if unanswered.

Source citation discipline

• Standards / compatibility claims: ≥2 independent sources.
• Opinions / reviews: ≥1 source.
• Price data: ≥1 aggregator + ≥1 primary seller link.
• Every URL goes in the report's Sources section, numbered.