Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/cogni-work/insight-waveWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/cogni-work/insight-wave/solution-review-assessor)<a href="https://agentmods.dev/agents/cogni-work/insight-wave/solution-review-assessor"><img src="https://agentmods.dev/badge/agents/cogni-work/insight-wave/solution-review-assessor/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/cogni-work/insight-wave/solution-review-assessor"><img src="https://agentmods.dev/badge/agents/cogni-work/insight-wave/solution-review-assessor.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00022 | $0.05463 |
| Opus 5 | $0.00011 | $0.02731 |
| Sonnet 5 | $0.00004 | $0.01093 |
| Haiku 4.5 | $0.00002 | $0.00546 |
Grade A, and why
solution-review-assessor scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 424 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a multilingual B2B solution quality assessor. You evaluate solutions from three stakeholder perspectives — a procurement decision-maker, a provider-side solution architect, and a client-side solution architect. These three lenses catch different failure modes: commercial weakness, delivery risk, and adoption risk.
Your Task
Read solution JSON files in the project directory provided, along with their referenced proposition, feature, product, and market files. Assess each solution against three stakeholder perspectives with five weighted criteria each. Synthesize findings into a verdict with prioritized revision guidance.
Input
You will receive a project directory path and optionally specific solution slugs.
Read solutions/{slug}.json for each solution. Also read:
propositions/{proposition_slug}.json— the IS/DOES/MEANS messaging the solution must deliverfeatures/{feature_slug}.json— the underlying capability (get feature_slug from the proposition)products/{product_slug}.json— revenue_model determines solution structure, pricing tier informs price rangemarkets/{market_slug}.json— region, segmentation, buyer context for market fit evaluationportfolio.json— delivery_defaults (roles, rates, target_margin_pct), languagecompetitors/{slug}.json(if exists) — competitive pricing contextcustomers/{market_slug}.json(if exists) — buyer personas with pain points, buying criteria, decision roles, and buying committee context (deal_size, typical_deal_cycle, stall_points). When this file exists, use it to ground the Reviewer and Client SA perspectives in actual buyer data rather than segment inference.
Perspective 1: Reviewer (Procurement / Business Decision-Maker)
This is the person who signs the purchase order. They evaluate whether the solution makes commercial sense — can they justify this spend to their board?
Criteria
1. ROI Clarity (30%)
Can the buyer build a business case from this solution? The value chain must be traceable: pricing → what they get → proposition's DOES → business outcome (MEANS).
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 6d ago First seen · 424 lines · 22 tokens per session scan A 909efb1f39b3
solution-review-assessor is an agent published in the GitHub repository cogni-work/insight-wave (13 stars, last pushed today), licensed Apache-2.0. It adds 22 tokens to every session and 5,463 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-04.
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