10 AI Prompts to Decode Any Government Solicitation in 30 Minutes
You get the SAM.gov notification. You click through. There's the base solicitation — a 60-page PDF. Then three amendments. A Performance Work Statement in a separate Word doc. A pricing template in Excel. A Quality Assurance Surveillance Plan. Two appendices. A wage determination. A past performance questionnaire buried in a ZIP file. That's not one document. That's twelve. And you need to make sense of all of them before you can decide if this is even worth pursuing — let alone start writing. These 10 prompts will help you pull the critical information out of any federal solicitation using ChatGPT or similar tools. Then we'll show you how CLEATUS does it without prompts at all — by scanning every page of every document and automatically organizing everything into a structured Uniform Contract Breakdown (Sections A–M) before you even start reading.
TL;DR
- Government solicitations aren't a single document. They're a package — base RFP, amendments, attachments, exhibits, wage determinations, pricing templates — scattered across a dozen or more files with requirements cross-referenced between them.
- These 10 prompts help you extract what matters — scope, deadlines, evaluation criteria, compliance requirements, and pricing structure — using ChatGPT or any general-purpose AI tool.
- But prompts are still a workaround. You're pasting documents one at a time. You're managing token limits. You're manually cross-referencing outputs across separate conversations. You're the integration layer.
- CLEATUS's Contract Breakdown scans every page of every document — PDFs, Word files, Excel spreadsheets, scanned images — using OCR and local models, then automatically restructures the entire solicitation package into the Uniform Contract Format (Sections A–M) with scope, pricing, deadlines, and evaluation criteria organized and summarized.
- The result: What takes 2–3 hours of prompting and manual assembly takes minutes with purpose-built AI. And because the AI agent works from structured, verified data instead of copy-pasted text fragments, accuracy goes up and hallucination drops to near zero.
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Why Solicitation Analysis Is the Real Bottleneck
Here's something that doesn't get talked about enough: the hardest part of responding to a solicitation isn't writing the proposal. It's figuring out what the government is actually asking for.
It sounds simple. It's not. Federal solicitations follow the Uniform Contract Format defined in FAR 15.204-1 — 13 sections labeled A through M. But the format is a starting point, not a guarantee of clarity. In practice, every solicitation is a scavenger hunt across multiple documents.
The Statement of Work lives in Section C — unless it's been moved to Section J as an attachment. The evaluation criteria are in Section M — but the proposal instructions in Section L may reference additional requirements that change how you should weight your response. Compliance requirements might be in Section H (Special Contract Requirements), Section I (Contract Clauses), or buried in an appendix that's listed in Section J but not explicitly called out anywhere else.
The majority of rejected proposals fail due to missed requirements or incomplete submissions — not because the contractor lacked capability, but because they missed a requirement buried in an attachment they didn't fully read or a clause cross-referenced between two separate documents.
Generic AI can help. These prompts will get you started. But understand upfront: you are the integration layer. You're the one pasting text, managing token limits, cross-referencing outputs, and verifying that the AI didn't hallucinate a clause that doesn't exist.
The 10 Prompts
Prompt 1: The 60-Second Executive Summary
"Read the attached solicitation documents. Provide a one-page executive summary that includes: (1) the issuing agency and contracting office, (2) the solicitation number, (3) the contract type (FFP, T&M, cost-plus, IDIQ, etc.), (4) the NAICS code and size standard, (5) any set-aside designation, (6) the estimated contract value or ceiling, (7) a 3-sentence description of the scope of work, and (8) the proposal due date. Format this as a briefing document I can share with leadership for a quick go/no-go conversation."
Why it matters: This is your first pass — the 60-second scan that tells you whether to keep reading or move on. Most capture managers do this manually by skimming the SF-33 (Section A), the CLINs (Section B), and the first few paragraphs of Section C. This prompt compresses that into a structured output.
Where generic AI struggles: If the solicitation spans multiple documents (base RFP plus amendments plus attachments), ChatGPT can't ingest all of them simultaneously. You'll need to paste the SF-33 and Section C separately and manually combine the results. If the contract value isn't stated explicitly — which it often isn't — the AI may either skip the field or hallucinate a number.
Prompt 2: Extract Every Deadline and Key Date
"Scan the entire solicitation, including all amendments and attachments. Extract every date and deadline mentioned, including: questions due date, site visit dates, proposal submission deadline (date and time, with timezone), anticipated award date, period of performance start date, option period dates, and any interim milestone dates. Present these in a chronological table. Flag any dates that appear to conflict with each other."
Why it matters: Missing a deadline is the fastest way to disqualify yourself. But deadlines in government solicitations aren't always in one place. The submission deadline is usually on the SF-33. The questions deadline might be in Section L. Performance milestones could be in Section F. Amendment deadlines show up in the amendment cover pages. This prompt forces a comprehensive extraction.
Where generic AI struggles: Amendments frequently modify deadlines set in the original solicitation. If you paste documents in the wrong order or miss an amendment, the AI will give you the original (now incorrect) dates. There's no built-in awareness of which document supersedes which.
Prompt 3: Map Section L Instructions to Section M Evaluation Criteria
"Extract the complete proposal preparation instructions from Section L and all evaluation criteria from Section M. Create a two-column mapping table: Column 1 lists each Section L instruction (with the specific subsection reference), and Column 2 maps it to the corresponding Section M evaluation factor and subfactor. Identify any Section L instructions that don't have a clear corresponding evaluation criterion, and any Section M criteria that aren't addressed in Section L. Flag mismatches, gaps, and ambiguities."
Why it matters: This is the most important analytical step in solicitation analysis, and it's the one that separates experienced capture managers from everyone else. Section L tells you what to submit. Section M tells you how it will be scored. When they don't align perfectly — and they frequently don't — you have a problem that needs to be resolved before you start writing.
Where generic AI struggles: This requires cross-document reasoning. Section L might say "provide a staffing plan" while Section M evaluates "management approach." Are those the same thing? A contracting officer would say yes. ChatGPT might not make that connection without additional prompting. You'll likely need 2–3 follow-up prompts to refine the mapping.
Prompt 4: Build a Zero-Draft Compliance Matrix
"Using Section L, Section M, Section C (Statement of Work / PWS), and any other relevant sections, generate a compliance matrix with the following columns: (1) Requirement ID or reference, (2) Requirement description, (3) Source section and page number, (4) Proposal volume/section where the response should go, (5) Compliance status (leave blank for now), and (6) Notes on any ambiguity or risk. Include every 'shall,' 'must,' and 'will' statement from the PWS as individual line items."
Why it matters: The compliance matrix is the backbone of every winning proposal. It's also the most tedious document to build manually. An experienced proposal manager can take 4–8 hours to build a comprehensive compliance matrix for a complex solicitation. This prompt gives you a zero-draft starting point that you can validate and refine.
Where generic AI struggles: This is where token limits become a real problem. A 200-page solicitation won't fit in a single ChatGPT session. You'll need to break it into sections, generate partial matrices, and manually combine them — introducing the risk of duplicated or missed requirements. The AI also tends to miss requirements that are stated indirectly or by reference to external standards.
Prompt 5: Analyze the Pricing Structure and CLINs
"Review Section B (Supplies or Services and Prices/Costs) and any pricing-related attachments. Identify: (1) the contract pricing type for each CLIN (FFP, T&M, cost-plus, etc.), (2) all Contract Line Item Numbers with their descriptions, (3) any optional CLINs or option years, (4) whether the government has provided a pricing template or if one must be created, (5) any ceiling or floor pricing constraints, and (6) labor category requirements with any specified wage determinations (SCA or Davis-Bacon). Summarize the pricing structure in plain language."
Why it matters: Pricing strategy starts with understanding the CLIN structure. Mixed pricing types (e.g., FFP for base operations with T&M for surge support) require different cost-building approaches. Missing an option year CLIN or misunderstanding the pricing type can make your entire cost volume non-compliant.
Where generic AI struggles: Pricing templates and CLIN structures are often in Excel attachments that ChatGPT can't read natively. You'll need to convert them to text or CSV first. Wage determination cross-references (e.g., "See SCA WD 2015-4281, Revision 25") require lookup against external government databases that generic AI can't access.
Prompt 6: Identify Hidden Requirements in Attachments and Section J
"Review the List of Attachments in Section J and all referenced appendices, exhibits, and supplementary documents. For each attachment, provide: (1) the document title and reference number, (2) a brief summary of what it contains, (3) whether it contains any requirements or deliverables not mentioned in the main solicitation body, and (4) whether any certifications, forms, or templates must be completed and submitted with the proposal. Flag any attachments that are listed in Section J but not included in the solicitation package."
Why it matters: This is where proposals die quietly. Section J often lists 10–20+ attachments, and contractors routinely miss requirements buried in appendices — a quality assurance surveillance plan template that must be completed, a past performance questionnaire that needs to be sent to references, a cybersecurity attestation that isn't mentioned in the main body. If it's in Section J, it's part of the solicitation.
Where generic AI struggles: Attachments are typically separate files — PDFs, Word documents, Excel spreadsheets — that you can't paste into a single prompt. This means you're managing each attachment as a separate conversation, then manually cross-referencing against the Section J list. If an attachment is listed but missing from the solicitation package (which happens more often than it should), the AI won't flag it unless you tell it what to look for.
Prompt 7: Decode Special Contract Requirements (Section H)
"Review Section H (Special Contract Requirements) and identify all requirements that go beyond the standard FAR clauses in Section I. For each requirement, explain: (1) what the contractor must do, (2) when it must be done (prior to award, at contract start, ongoing, etc.), (3) whether it requires a specific deliverable or certification, and (4) any financial or operational impact. Pay special attention to security clearance requirements, organizational conflict of interest provisions, key personnel requirements, and transition-in/transition-out obligations."
Why it matters: Section H is where agencies put the requirements that don't fit neatly elsewhere — and it's where some of the most operationally significant obligations live. Security clearance requirements, CMMC compliance levels, OCI mitigation plans, and mandatory subcontracting plans are often specified here. Missing a Section H requirement doesn't just hurt your proposal score — it can make you non-responsive.
Where generic AI struggles: Section H requirements often reference external standards or regulations by number (e.g., "Contractor shall comply with DFARS 252.204-7012" or "Facility clearance at the Secret level required within 60 days of award"). ChatGPT can explain what DFARS 252.204-7012 covers in general terms, but it can't assess whether your company meets the requirement or what it would take to comply. That assessment still falls to you.
Prompt 8: Assess Past Performance and Experience Requirements
"From Sections L and M, extract all past performance and experience requirements. Identify: (1) the number of past performance references required, (2) the minimum contract value or scope thresholds for acceptable references, (3) how recent the past performance must be (typically last 3–5 years), (4) whether the government will use CPARS data or request separate questionnaires, (5) whether subcontractor past performance is acceptable, (6) the specific relevance criteria (scope, size, complexity, agency type), and (7) how past performance is weighted relative to other evaluation factors. Note any language suggesting that 'neutral' past performance (no record) may be treated differently than 'satisfactory' performance."
Why it matters: Past performance is often the hardest evaluation factor to improve on a short timeline. If the solicitation requires three references at $5M+ in the same NAICS code within the last three years, and you only have two — that's a strategic issue that changes your entire bid decision, not something you solve in the proposal writing phase.
Where generic AI struggles: The AI can extract what's written, but it can't assess your past performance against the requirements. It also can't access CPARS to check your ratings or determine whether a specific reference contract matches the relevance criteria. This is analysis, not extraction — and generic AI gives you extraction only.
Prompt 9: Flag Potential Risks, Conflicts, and Ambiguities
"Review the entire solicitation and identify: (1) any conflicts or contradictions between sections (e.g., Section L says 'no page limit' but Section M references 'conciseness of response'), (2) ambiguous requirements that could be interpreted multiple ways, (3) unusually restrictive requirements that may limit competition or favor an incumbent, (4) requirements that appear to have changed between the original solicitation and any amendments, (5) areas where the solicitation references documents or standards that are not included, and (6) any requirements that create significant operational, financial, or compliance risk. For each issue, suggest a clarification question that could be submitted to the Contracting Officer."
Why it matters: The best capture managers don't just read solicitations — they read between the lines. Ambiguities are opportunities to ask clarification questions that can reshape the competitive landscape. Contradictions between sections, if not resolved before proposal submission, can lead to protest-worthy situations. And overly restrictive requirements are worth flagging because they may indicate the solicitation was written around a specific incumbent.
Where generic AI struggles: This is the highest-judgment prompt on the list. Generic AI can find explicit contradictions (Section L says 10 pages, Section M says 15), but it's much worse at detecting subtle signals — like a requirement for "proprietary methodology X" that only one company offers, or a transition timeline that's unrealistically short for anyone except the incumbent. This kind of analysis requires GovCon domain expertise that ChatGPT simply doesn't have.
Prompt 10: Generate Clarification Questions for the Contracting Officer
"Based on your analysis of this solicitation, generate a list of 10 clarification questions to submit to the Contracting Officer before the questions deadline. Prioritize questions that: (1) resolve ambiguities that affect your proposal strategy, (2) clarify conflicting requirements between sections, (3) request missing attachments or referenced documents, (4) seek confirmation on evaluation methodology or weighting, and (5) address scope boundaries that could affect pricing. Format each question with a reference to the specific section, page, and paragraph being questioned. Do not ask questions whose answers are clearly stated elsewhere in the solicitation."
Why it matters: Smart clarification questions serve two purposes. Tactically, they get you answers you need. Strategically, they signal to the Contracting Officer that you've done your homework — and they can sometimes nudge the agency to issue amendments that level the competitive playing field.
Where generic AI struggles: The AI tends to generate questions that are either too generic ("Could you clarify the evaluation criteria?") or that ask about things already answered in the solicitation — which makes you look unprepared rather than diligent. You'll need to heavily edit the output and cross-reference against the actual solicitation before submitting anything.
The Pattern You've Probably Noticed
If you've been reading carefully, you noticed the same issue coming up in every single prompt:
Generic AI makes you do all the hard work.
You're copying and pasting documents — in chunks, because they don't fit in one session. You're managing token limits. You're uploading attachments separately and manually cross-referencing. You're verifying every output because the AI might hallucinate a clause, miss an amendment, or fabricate a requirement. You're the compliance layer, the integration layer, and the quality control layer — all at once.
These prompts help. They give you a framework. They save time compared to doing everything manually. But they don't solve the structural problem: ChatGPT has never seen a government solicitation before you paste one in. It doesn't know what the Uniform Contract Format is. It doesn't know that Section J attachments are separate files. It doesn't know which document supersedes which when amendments modify the original RFP.
That's the gap that purpose-built GovCon AI fills.
How CLEATUS Eliminates the Need for Solicitation Prompts
Here's what actually happens when you open a solicitation in CLEATUS — no prompting required.
Automatic Contract Breakdown: Sections A Through M
CLEATUS scans every single page in every single document of the solicitation — the base RFP, all amendments, every attachment, every exhibit. Using OCR and specialized local models, it extracts all critical information and automatically categorizes it into the Uniform Contract Format (Sections A through M).
The result is a clean, navigable breakdown:
- Section A — Solicitation form, agency, contracting office, solicitation number
- Section B — CLIN structure, pricing type, option periods
- Section C — Full scope of work, key deliverables, performance standards
- Section D — Packaging and marking requirements
- Section E — Inspection and acceptance criteria
- Section F — Delivery schedule, performance periods, milestones
- Section G — Contract administration contacts, invoicing instructions
- Section H — Special requirements, security, OCI provisions, key personnel
- Section I — All incorporated FAR/DFARS clauses
- Section J — Attachments, exhibits, and supplementary documents
- Section K — Certifications and representations
- Section L — Proposal instructions, format requirements, page limits
- Section M — Evaluation criteria, weighting, award methodology
You don't paste anything. You don't write a prompt. You don't manage token limits or worry about which amendment supersedes which. The platform has already done the work — and it's organized in the exact structure that contracting officers and proposal managers think in.
Why This Matters for AI Accuracy
This isn't just about convenience. CLEATUS's Contract Breakdown fundamentally changes how the AI agent processes solicitation data.
When you paste chunks of an RFP into ChatGPT, the AI is working from unstructured, incomplete text with no awareness of what's in the other chunks you haven't pasted yet. It can't cross-reference Section L against Section M if they're in different conversations. It can't verify that an attachment listed in Section J is actually included in the document package.
CLEATUS structures the data before the AI reasons about it. The agent works from a complete, verified, organized representation of the entire solicitation — which dramatically improves accuracy and virtually eliminates the hallucination problem that plagues generic AI tools when they're asked about specific contract requirements.
The difference in practice: With ChatGPT, you spend 2–3 hours prompting, pasting, verifying, and cross-referencing to get a partial picture of a solicitation. With CLEATUS, you click into an opportunity and the Contract Breakdown is already waiting — complete, structured, and ready for your review. You're reading organized intelligence, not raw text.
From Breakdown to Action: The Full Workflow
The Contract Breakdown is the foundation, but it's not the end of the workflow. Once the solicitation is structured:
Chat directly with the solicitation. Use CLEATUS's GovCon Copilot to ask questions about the RFP and get instant answers with page-level citations — not hallucinated responses. Ask "What security clearance level is required?" and get the answer traced to the exact page and paragraph.
Auto-generate a compliance matrix. CLEATUS maps every requirement across all sections — including attachments — into a structured compliance matrix aligned to Section L/M. What takes hours of manual extraction (or multiple rounds of ChatGPT prompting) happens in minutes.
Accelerate your proposal. The AI Proposal Suite uses the structured breakdown to generate Section L/M-aligned outlines, pull relevant past performance from your uploaded history, and create compliant first drafts grounded in the actual evaluation criteria.
Make better bid decisions. With the solicitation fully understood in minutes instead of hours, your team can make faster, more confident go/no-go decisions — and spend their time on opportunities worth pursuing.
The Numbers Behind the Difference
| Task | ChatGPT + These Prompts | CLEATUS Contract Breakdown |
|---|---|---|
| Solicitation ingestion | Manual copy-paste in chunks | Full OCR scan of all documents automatically |
| Section A–M organization | You manually structure outputs | Automated Uniform Contract Breakdown |
| Cross-referencing sections | Multiple sessions, manual reconciliation | Built-in — agent sees entire solicitation at once |
| Amendment handling | Manual tracking, risk of stale data | Amendments integrated automatically |
| Compliance matrix | Multiple prompts + manual assembly | Auto-generated, requirement-traced |
| Time to full understanding | 2–3 hours of active work | Minutes |
| Hallucination risk | High — unstructured input, no verification | Minimal — structured data, cited sources |
What Contractors Are Experiencing
The solicitation analysis advantage is compounding across every customer we work with:
D2 Government Solutions, an SDVOSB with 300+ employees, was spending days reading and parsing large solicitation documents before CLEATUS. With the Contract Breakdown and GovCon Copilot, they achieved 75% faster opportunity discovery and 80% reduction in draft development time — tripling their proposal output with the same team.
Operation Hired replaced their "cluttered" mix of generic AI tools and spreadsheets with CLEATUS and achieved 6x proposal throughput in 10 weeks. The GovCon Copilot became their "first-read" expert — breaking down solicitations instantly and letting the team ask complex questions with cited answers.
MST Maritime went from 3 proposals per month to 10+, with 3x faster proposal development and 75% faster opportunity discovery. Same team. Same resources. Different platform.
– John Garnish, Business Development Lead, D2 Government Solutions
Stop Pasting. Start Understanding.
These 10 prompts are a genuine upgrade over reading solicitations manually. Use them. They'll save you time.
But if you're analyzing more than a few solicitations per month — and especially if you're a small or mid-sized firm where every BD hour counts — the prompt-based workflow hits a ceiling fast. You're still the integration layer. You're still the compliance checker. You're still managing the gap between what generic AI can do and what GovCon actually requires.
CLEATUS was built to close that gap. The Contract Breakdown scans every page, organizes every section, and gives your team a structured, navigable, accurate foundation for every pursuit — in minutes, not hours. And the AI agent works from that foundation to deliver cited answers, compliance matrices, and proposal drafts that are grounded in the actual solicitation, not hallucinated from fragments.
Your competitors are making this switch. The numbers prove it works. The question is how many more solicitations you're going to decode the hard way before you try it.
Ready to see the difference? Book a live demo and see how CLEATUS turns 200-page solicitations into structured intelligence in minutes.
Already using ChatGPT for solicitation analysis? Check out our guide to the 10 AI Prompts Every Government Contractor Should Know — and then see why you won't need them anymore.
Frequently Asked Questions
Further Reading
- Stop Prompt Engineering. Start Winning Contracts.
- FPDS Is Gone. Here's How Smart Contractors Are Accessing Government Contract Data Now.
- Agentic AI for GovCon Capture Management in 2026
- GovCon AI in 2026: How CLEATUS Is Helping Contractors Find, Win, and Deliver
Customer Stories
- How D2 Government Solutions Tripled Growth Without Adding Staff
- How Operation Hired Achieved 6× Proposal Output with CLEATUS AI
- How MST Maritime Quadrupled Proposal Output with CLEATUS AI
About CLEATUS
CLEATUS is an AI-powered government contracting platform that helps contractors find opportunities, analyze requirements, track competitors, and win more contracts — at a fraction of traditional capture costs. We aggregate federal, state, local, and city opportunities; our GovCon Copilot analyzes solicitations and your internal documents to deliver actionable market intelligence that drives revenue growth.