Rfp Responder
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 (MA...
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 proof point, articulating 3-5 win-themes that ladder up across requirements, and producing a Shipley-derived winrate estimate that informs a bid / no-bid / partner-bid recommendation. For Bid Managers, Proposal Leads, Directors of Sales, and Sales Engineers at the response-strategy moment. Surfaces GAP requirements explicitly — never invents claims. NOT free-form proposal narrative authoring, NOT contract redline, NOT marketing collateral.
Install
Quick install
npx skills add https://github.com/alirezarezvani/claude-skills/tree/main/commercial/skills/rfp-respondernpx skills add alirezarezvani/claude-skills --skill rfp-responder --agent claude-codenpx skills add alirezarezvani/claude-skills --skill rfp-responder --agent cursornpx skills add alirezarezvani/claude-skills --skill rfp-responder --agent codexnpx skills add alirezarezvani/claude-skills --skill rfp-responder --agent opencodenpx skills add alirezarezvani/claude-skills --skill rfp-responder --agent github-copilotnpx skills add alirezarezvani/claude-skills --skill rfp-responder --agent windsurfMore install options
Shorthand — useful for multi-skill repos:
npx skills add alirezarezvani/claude-skills --skill rfp-responderManual — clone the repo and drop the folder into your agent's skills directory:
git clone https://github.com/alirezarezvani/claude-skills.gitcp -r claude-skills/commercial/skills/rfp-responder ~/.claude/skills/rfp-responder
Purpose
Help Bid Managers, Proposal Leads, and Directors of Sales answer five questions at the response-strategy moment:
- What is this RFP actually asking? (parse sections, tag every requirement MANDATORY / WEIGHTED / NICE-TO-HAVE, extract scoring criteria, surface deadlines and format constraints)
- 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)
- What is our win-theme strategy? (Shipley method: 3-5 themes that ladder up across requirements, not generic value-prop bullets)
- 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)
- 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.json
Step 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.md
Hard 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 markdown
No-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 any script runs. Recommended answer + canon citation per question. Never bundled.
- "What's your STRONG / PARTIAL / GAP split on the MANDATORY requirements?"**
- "Is there an incumbent, and how strong is their position?"
- "Did you enter the conversation before or after the RFP issued?"
- "What are your 3-5 win-themes, and does each thread through ≥2 requirements?"
- "For every claim in the response, can you name the verifiable source?"
- "What's the bid / no-bid threshold you committed to BEFORE seeing this RFP?"
- "What does the buyer's evaluation team actually score on?"
Walk depth-first. Lock 1-3 before opening 4-7. After all 7 are answered, invoke rfp_parser.py → response_drafter.py → winrate_predictor.py in sequence. If question 6 lands on "we don't have a threshold," set one now or no-bid.
SKILL.md source
--- name: rfp-responder description: 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 (MA... --- # 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. ```bash python scripts/rfp_parser.py --input rfp.md --output json > parsed.json ``` ### Step 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. ```bash python scripts/response_drafter.py --input draft_input.json --output markdown > matrix.md ``` **Hard 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. ```bash python scripts/winrate_predictor.py --input deal_context.json --profile enterprise-software --output markdown ``` **No-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 audit - `scripts/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 Newman - `references/rfp_strategy_canon.md` — FAR, GSA, Forrester, Gartner, Bain, McKinsey, B2B International on RFP win-rates and buyer behavior - `references/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 any script runs. Recommended answer + canon citation per question. Never bundled. 1. **"What's your STRONG / PARTIAL / GAP split on the MANDATORY requirements?"** Recommended: STRONG ≥ 70% on MANDATORY before bidding. PARTIAL/GAP on any MANDATORY = either close the gap pre-submission or no-bid. Canon: Shipley *Proposal Guide v6* — capture-management discipline, "Pgw (probability of win) is bounded by your weakest MANDATORY." 2. **"Is there an incumbent, and how strong is their position?"** Recommended: strong incumbent (3+ years, no displacement event) drops base winrate ~30%. Don't bid without a named displacement trigger. Canon: Forrester B2B-RFP research — incumbents win 70-80% of renewal RFPs absent a named failure event. 3. **"Did you enter the conversation before or after the RFP issued?"** Recommended: late-entry (after RFP issued, no prior engagement) drops winrate ~15% and signals the RFP was scoped to someone else's strengths. Canon: Tom Searcy + Henry DeVries *How to Win Big Business* — "If you didn't help write the RFP, you're column fodder." 4. **"What are your 3-5 win-themes, and does each thread through ≥2 requirements?"** Recommended: themes that appear in only one requirement are decorative. Themes must ladder up across MANDATORY + WEIGHTED sections. Canon: Shipley *Capture Guide* — win-themes are the buyer-side answer to "why us" across the evaluation criteria, not seller-side feature lists. 5. **"For every claim in the response, can you name the verifiable source?"** Recommended: every claim → case study / certification / customer reference / technical attestation / benchmark. Unsourced claims = GAPs. Canon: APMP BoK — "Substantiation: every assertion in a proposal must be backed by evidence the evaluator can independently verify." 6. **"What's the bid / no-bid threshold you committed to BEFORE seeing this RFP?"** Recommended: pre-committed threshold (e.g., winrate ≥ 25%, STRONG ≥ 70% on MANDATORY, named champion). Post-hoc rationalization is how teams end up bidding 5% pursuits. Canon: Bain RFP-win-rate studies — disciplined bid/no-bid gates lift win-rate from ~15% to ~35%. 7. **"What does the buyer's evaluation team actually score on?"** Recommended: if the RFP discloses scoring criteria, weight your response effort proportionally. If undisclosed, ask. If you can't ask, that itself is a relationship-deficit signal. Canon: Strategic Proposals proposal-management research — evaluators score on the rubric they were given, not on your narrative. Walk depth-first. Lock 1-3 before opening 4-7. After all 7 are answered, invoke `rfp_parser.py` → `response_drafter.py` → `winrate_predictor.py` in sequence. If question 6 lands on "we don't have a threshold," set one now or no-bid.
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