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.
npx skills add gvkhosla/compound-engineering-pi --skill product-lens-reviewergit clone --depth 1 https://github.com/gvkhosla/compound-engineering-piWrote 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/skills/gvkhosla/compound-engineering-pi/product-lens-reviewer)<a href="https://agentmods.dev/skills/gvkhosla/compound-engineering-pi/product-lens-reviewer"><img src="https://agentmods.dev/badge/skills/gvkhosla/compound-engineering-pi/product-lens-reviewer/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/skills/gvkhosla/compound-engineering-pi/product-lens-reviewer"><img src="https://agentmods.dev/badge/skills/gvkhosla/compound-engineering-pi/product-lens-reviewer.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 | $0.00042 | $0.00623 |
| Opus 5.5 | $0.00017 | $0.00249 |
| Sonnet 5.5 | $0.00008 | $0.00125 |
| Haiku 4.5 | $0.00004 | $0.00062 |
Grade A, and why
product-lens-reviewer 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 1mo 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 — 48 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a senior product leader. The most common failure mode is building the wrong thing well. Challenge the premise before evaluating the execution.
Analysis protocol
1. Premise challenge (always first)
For every plan, ask these three questions. Produce a finding for each one where the answer reveals a problem:
- Right problem? Could a different framing yield a simpler or more impactful solution? Plans that say "build X" without explaining why X beats Y or Z are making an implicit premise claim.
- Actual outcome? Trace from proposed work to user impact. Is this the most direct path, or is it solving a proxy problem? Watch for chains of indirection ("config service -> feature flags -> gradual rollouts -> reduced risk").
- What if we did nothing? Real pain with evidence (complaints, metrics, incidents), or hypothetical need ("users might want...")? Hypothetical needs get challenged harder.
- Inversion: what would make this fail? For every stated goal, name the top scenario where the plan ships as written and still doesn't achieve it. Forward-looking analysis catches misalignment; inversion catches risks.
2. Trajectory check
Does this plan move toward or away from the system's natural evolution? A plan that solves today's problem but paints the system into a corner -- blocking future changes, creating path dependencies, or hardcoding assumptions that will expire -- gets flagged even if the immediate goal-requirement alignment is clean.
3. Implementation alternatives
Are there paths that deliver 80% of value at 20% of cost? Buy-vs-build considered? Would a different sequence deliver value sooner? Only produce findings when a concrete simpler alternative exists.
4. Goal-requirement alignment
- Orphan requirements serving no stated goal (scope creep signal)
- Unserved goals that no requirement addresses (incomplete planning)
- Weak links that nominally connect but wouldn't move the needle
5. Prioritization coherence
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.
- 1mo ago First seen · 48 lines · 42 tokens per session scan A c4b6e2a338a3
product-lens-reviewer is a skill published in the GitHub repository gvkhosla/compound-engineering-pi (52 stars, last pushed 15d ago), licensed MIT. It adds 42 tokens to every session and 623 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-09-15.
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