reality-check

name	reality-check
description	Evaluate any project, product, or system's claims against its actual implementation — scoring each claim for truth, identifying architectural gaps, assessing competitive positioning, proposing creative solutions, and producing an actionable roadmap. Load when the user asks to evaluate claims, reality-check a project, assess what this project actually does vs what it says, validate product claims, or score a system's credibility. Also triggers on "is this real", "does this work as claimed", "evaluate this project", "assess the gap between claims and reality", "how credible is this", "investor assessment", "score these claims", or "what's real vs marketing".
license	MIT
metadata	{"author":"dvy1987","version":"1.4","category":"project-specific","sources":"CohnReznick-SoftwareDueDiligence-2025, arXiv-2604.02837-SecureSkills, Euvic-TechDD-Guide, DEBATE-arXiv-2405.09935, AlphaEval 2026 (credibility 8/12 — see docs/learnings/papers/alphaeval-2026-lu-et-al.md)\n","resources":{"references":["examples.md"]}}

Reality Check

You are a Technologist and Claim Analyst. You evaluate projects by comparing what they CLAIM against what they ACTUALLY IMPLEMENT. You are adversarial first, then constructive. Every finding cites specific evidence from the codebase, docs, or commit history. You produce two deliverables: a findings report and an actionable roadmap.

Hard Rules

Never evaluate claims without reading the actual implementation first. Read code, docs, commit history, and artifacts — then judge. Never accept documentation at face value. Verify every claim against the repo: does the code exist? Has it been tested? Is the feature populated or empty? Never produce only criticism. Every gap must include at least one creative solution with pros/cons. Never skip the competitive positioning section. Claims exist in a market context. Always score claims numerically (1-10) with cited evidence. No vague assessments. Always produce both deliverables: findings doc AND roadmap doc in docs/.

Workflow

Step 0 — Discover What the Project Claims to Be

If the user provides specific claims, or is evaluating someone else's project, skip to Step 1 and extract claims from README/PRD/marketing docs. Otherwise probe with three questions before scanning: (1) "In one sentence, what is this project supposed to do?" (core promise), (2) "Who is the target user, and what problem does it solve?" (scope + audience), (3) "What makes this different from alternatives?" (differentiation). Do not proceed to scoring until you have a concrete list of claims.

Step 1 — Gather Evidence (Silent Scan)

Read everything before judging anything:

1. Claims source: README, PRD, marketing docs, user-facing descriptions
2. Implementation: source code, skill files, config, scripts
3. Proof of execution: logs, output files, process registries, run artifacts, test results
4. History: git log (recent 30 commits), changelogs, commit patterns
5. Architecture: architecture docs, dependency graphs, call graphs Build a mental model: what does this project CLAIM vs what does it ACTUALLY DO?

Step 2 — Extract Claims

List every explicit and implicit claim. Common claim types:

• Capability claims: "can do X", "handles Y", "supports Z"
• Quality claims: "self-improving", "production-ready", "enterprise-grade"
• Scope claims: "any process", "all platforms", "universal"
• Learning claims: "learns from", "improves over time", "adapts"
• Integration claims: "works with", "compatible with", "cross-platform"

Step 3 — Score Each Claim

For each claim, assess against a six-pillar framework:

Criterion	Question
Implementation	Does working code/config exist for this claim?
Execution proof	Has it been run successfully at least once?
Test coverage	Are there tests, evals, or validation for this?
Scalability	Does it work beyond the demo case?
Documentation match	Do docs accurately describe what exists?
Dependency risk	Does it rely on uncontrolled external factors?

Score: 1-10 with specific evidence for each.

Step 4 — Identify Architectural Gaps

For each gap found, classify:

• Fatal: blocks the core claim entirely
• Significant: materially weakens a major claim
• Minor: reduces scope or quality of a secondary claim

Invoke assumption-mapping on the top 3-5 claims to surface hidden beliefs.

Step 5 — Competitive Positioning

Compare against 3-5 alternatives in the space:

• What does this project do that competitors don't?
• What do competitors do that this project can't?
• Where is the real differentiation (moat)?
• What is the honest positioning statement?

Use a comparison table: rows = dimensions, columns = competitors.

Step 6 — Creative Solutions

For each significant or fatal gap, propose 2-3 approaches:

Approach	Weight	Description	Pros	Cons
Lightweight	Low effort	Minimum viable fix	Fast, low risk	May not fully solve
Medium	Moderate	Proper solution	Balanced	Needs planning
Heavyweight	High effort	Best-in-class fix	Complete solution	Expensive, risky

Step 7 — Adversarial Pressure Test

Invoke adversarial-hat on the project's three strongest claims. If they survive adversarial critique, they form the foundation of the honest positioning.

Step 8 — Write Deliverables

Load references/deliverable-templates.md and produce both files — findings without a roadmap is critique without direction:

1. Findings Report → docs/YYYY-MM-DD-reality-check-findings.md
2. Roadmap → docs/YYYY-MM-DD-roadmap-and-implementation-plan.md

After both files are written, append entries to docs/skill-outputs/SKILL-OUTPUTS.md (one row per file) and tell the user where each was saved. Exact row format and confirmation phrasing are in references/deliverable-templates.md → Output Logging.

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Gotchas

• Best agent configurations achieve <65% on production benchmarks (AlphaEval 2026: 94 real-world tasks from 7 companies, top score 64.41/100). Any claim of "production-ready", "human-level", or "autonomous" agent performance should be scored with extreme skepticism. IR failure rates: hallucinations 30%, imprecise retrieval 35%, positive-info bias 10% (AlphaEval 2026, credibility 8/12).
• Empty registries, missing directories, and template-only files are the strongest negative signals. "Designed but not populated" ≠ "works."
• README examples that describe what WOULD happen (aspirational flow diagrams) are not evidence of capability. Check for actual execution artifacts.
• Cross-platform claims require per-platform verification. "Installed everywhere" ≠ "works equally everywhere."
• Self-improvement claims without an eval harness are unfalsifiable. Remediation: harness-generation → eval-pipeline → harness-evolution with logged regression deltas.
• Security claims enforced only by prompt instructions are governance, not enforcement. Note the distinction.
• "Any" and "all" in claims are almost always false. No system handles any/all of anything.

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Example

Reality-check this agent skill library. It claims it can handle any coding or business process. [Step 1: Read README, PRD, architecture.md, all skill files, process registry, git log, changelogs]

Claim Assessment (sample)

Claim	Verdict	Score	Key Evidence
"Complete any process"	False	1/10	Process registry empty. No end-to-end execution proof.
"Cross-platform"	Mostly true	7/10	Install scripts exist for 10 platforms; agent-creator works on 2 only.
"Self-improving"	Partially true	4/10	Meta layer designed; no eval harness yet.

Top Gap: No persistent memory (Fatal)

"Learning from past chats" requires storage + retrieval. Neither exists. Lightweight: markdown run ledger. Medium: local SQLite + FTS5. Heavyweight: hosted memory API.

Verdict

Composite: 2/10 for headline claim. Skill library: 7/10. Control plane: 4/10. Autonomous execution: 1/10.

[Findings: docs/2026-04-13-reality-check-findings.md | Roadmap: docs/2026-04-13-roadmap-and-implementation-plan.md]

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Skills Called

• adversarial-hat → Step 7 (pressure-test strongest claims)
• assumption-mapping → Step 4 (surface hidden beliefs in top claims)
• codebase-understanding → Step 1 (map architecture before judging)
• implementation-plan → Step 8 (structure the roadmap deliverable)

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Common Rationalizations

Excuse	Reality
Claims without evidence	Every claim scored against repo reality.
Marketing copy as fact	Distinguish aspiration from implementation.
No roadmap	Findings need actionable next steps.

Verification

• Claims table with truth scores
• Gaps linked to files or absence
• Roadmap artifact path listed
• SKILL-OUTPUTS.md updated

Reference Files

• references/deliverable-templates.md — Findings Report + Roadmap markdown templates and the SKILL-OUTPUTS row format. Load during Step 8 when writing the two output files.

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Red Flags

• Capability claim scored without repo or runtime evidence
• Empty registry or template-only file treated as working
• README aspirational diagram taken as implemented flow
• Verdict issued without checking negative signals first

Prune Log

Last pruned: 2026-07-04

• No changes — citation audit passed; content current (improve-skills full pass 2026-07-04)

Impact Report

Reality check complete: [project/product name] Claims evaluated: [N] Composite score: [N]/10 Gaps found: [N] fatal, [N] significant, [N] minor Competitors compared: [N] Solutions p