rfp-responder – Security skill for AI agents
Use when an RFP, RFI, RFQ, security questionnaire, vendor questionnaire, or proposal request arrives and the team needs a structured response — parsing multi-section buyer-dictated requirements (MANDATORY vs WEIGHTED vs NICE-TO-HAVE), building a Shipley-method proof-point matrix mapping each requirement to a verifiable
Install the rfp-responder skill with one command
Pick the tool you use, copy the command and paste it in your terminal. The skill lands in that tool's skills folder and is ready in your next session.
Claude Code
mkdir -p ~/.claude/skills && curl -fsSL https://skill.dn1nguoi.com/z/rfp-responder-c61fd.tgz | tar xz -C ~/.claude/skills
Call it in Claude Code: /rfp-responder – then describe the task you want done.
Codex
mkdir -p ~/.codex/skills && curl -fsSL https://skill.dn1nguoi.com/z/rfp-responder-c61fd.tgz | tar xz -C ~/.codex/skills
Call it in Codex: $rfp-responder – then describe the task you want done.
Hermes Agent
mkdir -p ~/.hermes/skills && curl -fsSL https://skill.dn1nguoi.com/z/rfp-responder-c61fd.tgz | tar xz -C ~/.hermes/skills
Call it in Hermes Agent: /rfp-responder – then describe the task you want done.
DeepSeek
mkdir -p ~/.deepcode/skills && curl -fsSL https://skill.dn1nguoi.com/z/rfp-responder-c61fd.tgz | tar xz -C ~/.deepcode/skills
Call it in DeepSeek: /rfp-responder – then describe the task you want done.
SKILL.md content
rfp-responder
Purpose
Help Bid Managers, Proposal Leads, and Directors of Sales answer five questions at the response-strategy moment:
1. What is this RFP actually asking? (parse sections, tag every requirement MANDATORY / WEIGHTED / NICE-TO-HAVE, extract scoring criteria, surface deadlines and format constraints)
2. What is our true fit? (proof-point matrix per requirement: STRONG / PARTIAL / GAP, each backed by a verifiable source — case study, certification, customer quote, technical attestation, benchmark)
3. What is our win-theme strategy? (Shipley method: 3-5 themes that ladder up across requirements, not generic value-prop bullets)
4. What is our realistic winrate? (Shipley-derived factor model: fit, incumbent, relationship strength, decision-criteria alignment, late-entry, competitor count, deal size — produces estimate + confidence band)
5. Should we bid? (deterministic verdict: BID / PARTNER-BID / NO-BID with named factors driving the call)
The skill surfaces GAPs explicitly. Leadership decides whether to close them, partner around them, or no-bid. It never invents claims.
When to use
- A 30+ page RFP / RFI / RFQ has landed with a 7-14 day response deadline
- A security questionnaire (SIG, CAIQ, custom-buyer) needs structured Q&A — not prose
- The team is preparing a bid / no-bid review and needs a defensible winrate estimate
- Sales Engineering has a proof-point library but no system to map proofs to requirements
- Leadership wants to see fit % (STRONG / PARTIAL / GAP) before committing pursuit budget
- A late-entry opportunity needs honest assessment of the relationship deficit
Do not use for:
- Free-form proposal narrative authoring →
business-growth/contract-and-proposal-writer - Contract redline AFTER award →
c-level-advisor/general-counsel-advisor - Marketing collateral / category content →
marketing-skill/* - Discount approval on the awarded deal →
commercial/deal-desk - Pricing-model design for a new product →
commercial/pricing-strategist
Workflow
Step 1 — Parse the RFP
Drop the RFP markdown / text into scripts/rfp_parser.py. Output: structured JSON listing every requirement, tagged MANDATORY / WEIGHTED / NICE-TO-HAVE based on cue words (must / shall = MANDATORY; should / weighted scoring numbers = WEIGHTED; may / preferred / desired = NICE-TO-HAVE). Captures section structure, scoring criteria if disclosed, deadline, submission format constraints.
python scripts/rfp_parser.py --input rfp.md --output json > parsed.jsonStep 2 — Score fit per requirement
Fill assets/rfp_intake_template.md with your proof-point library (each proof tagged with type + verifiable source + which requirement-tags it covers) and proposed win-themes. Feed parsed RFP + intake into scripts/response_drafter.py. Output: proof-point matrix per requirement with STRONG / PARTIAL / GAP, win-theme injection, GAP audit.
python scripts/response_drafter.py --input draft_input.json --output markdown > matrix.mdHard rule: GAP requirements are surfaced, never invented around. Leadership reads the GAP audit and decides: close the gap, partner-bid, or no-bid.
Step 3 — Apply win-theme strategy
Shipley method: 3-5 themes that span requirements. Each theme answers "why us over the incumbent / competitor on the criteria the buyer named." response_drafter.py shows which themes thread through which requirements — a theme appearing in <2 requirements is decorative, not strategic, and gets flagged.
Step 4 — Estimate winrate
Feed deal context (fit %, incumbent strength, relationship, decision-criteria alignment, late-entry, competitor count, deal size vs. average) into scripts/winrate_predictor.py. Output: Shipley-derived estimate 0-100% + confidence band + factor breakdown + BID / PARTNER-BID / NO-BID verdict.
python scripts/winrate_predictor.py --input deal_context.json --profile enterprise-software --output markdownNo-bid threshold: estimate < 20% triggers automatic no-bid recommendation.
Step 5 — Decide
Take parsed RFP + proof-point matrix + GAP audit + winrate estimate into the go / no-go review. Skill does not commit pursuit budget — leadership does.
Scripts
scripts/rfp_parser.py— section + requirement extractor (regex + cue-word heuristics, stdlib only)scripts/response_drafter.py— proof-point matrix + win-theme injection + GAP auditscripts/winrate_predictor.py— Shipley-derived factor model + bid/no-bid verdict, industry-profile-tuned
All scripts: stdlib only (argparse, json, sys, pathlib, re, collections, statistics). --help and --sample work on all three.
References
references/shipley_method_canon.md— Shipley Proposal Guide v6, Shipley Capture Guide, APMP BoK, Tom Sant, Tom Searcy + Henry DeVries, Strategic Proposals research, Larry Newmanreferences/rfp_strategy_canon.md— FAR, GSA, Forrester, Gartner, Bain, McKinsey, B2B International on RFP win-rates and buyer behaviorreferences/rfp_anti_patterns.md— Shipley failure modes, APMP cases, Strategic Proposals research, federal loss reviews, MIT Sloan, Bain commercial-discipline, Gartner
Assumptions
- The RFP is the ground truth. If the buyer asked it, answer it — in the order they asked, in the format they specified. Re-organizing for narrative flow is for proposals, not RFPs.
- Proof points must be verifiable. A claim is only as strong as the case study, certification, customer reference, or technical attestation backing it. Unsourced claims become GAPs.
- Win-themes are buyer-side, not seller-side. "We're the leader in X" is a marketing claim; "Your operations team reduces incident MTTR by 60% with the same headcount" is a win-theme. Shipley canon, not optional.
- Winrate estimates are directional. The model is a discipline tool to force honest pursuit-qualification — not an oracle. Confidence band always wider than the point estimate suggests.
- Industry profiles tune base rates — government RFPs reward compliance discipline; enterprise SaaS rewards reference accounts; healthcare rewards regulatory + security depth.
- Late entry is a structural disadvantage. Entering after the RFP issued, with no relationship history, drops base rate ~15%. The skill names this, doesn't hide it.
Anti-patterns
- Inventing a proof point to fill a GAP. Hard rule violation. GAPs surface for leadership decision, not for prose-laundering. See
references/rfp_anti_patterns.md. - Responding to every RFP. Without a qualified bid / no-bid gate, the team burns capacity on <20% winrate pursuits and loses the 50%+ pursuits to lack of focus. Bain commercial-discipline research.
- Generic response with no win-theme. A proposal that could be sent verbatim by any competitor is decorative. Shipley failure mode #1.
- Missing a mandatory disqualifier late. FedRAMP / HIPAA / ISO 27001 / SOC 2 / on-shore data residency caught on Day 12 of a 14-day response = wasted pursuit. Parser surfaces these on Day 1.
- Answering the question YOU wanted asked. RFP responder discipline: answer what they asked, in their words, in their order. Re-framing belongs in cover letters, not in the compliance matrix.
- No compliance matrix. Every requirement should map to a response section + page number. Evaluators score on a matrix; respondents who don't provide one self-disqualify on traceability.
- Late-entry without acknowledging the relationship deficit. Entering cold against an incumbent with a 3-year relationship and no champion = sub-20% winrate. Pretending otherwise wastes Sales Engineering capacity.
- Treating WEIGHTED requirements like MANDATORY. Score-weighted requirements reward depth on the high-weight items, not uniform mediocrity across all. Shipley capture method.
Distinct from
business-growth/contract-and-proposal-writer— free-form narrative proposals where YOU set the structure (executive briefs, capability statements, unsolicited proposals). RFP-responder handles buyer-dictated structured Q&A where the buyer set the questions, sections, scoring criteria, and format. Different artifact, different decision logic.c-level-advisor/general-counsel-advisor— contract redline and IP/risk review AFTER award. RFP-responder operates BEFORE award, on the response strategy.- **
marketing-skill/*— external marketing assets (web copy, content, ASO, SEO, brand voice) for many-to-many audiences. RFP-responder produces a single-buyer artifact** with deterministic compliance requirements. commercial/deal-desk— per-deal discount routing on a closing opportunity. RFP-responder is pursuit-stage; deal-desk is close-stage.commercial/pricing-strategist— pricing-model design for a new product. RFP-responder consumes existing pricing as input to the commercial-terms section.
Forcing-question library (Matt Pocock grill discipline)
Walked one at a time before
… (full content is in the download package)
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