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 learnings-researchergit 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/learnings-researcher)<a href="https://agentmods.dev/skills/gvkhosla/compound-engineering-pi/learnings-researcher"><img src="https://agentmods.dev/badge/skills/gvkhosla/compound-engineering-pi/learnings-researcher/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/learnings-researcher"><img src="https://agentmods.dev/badge/skills/gvkhosla/compound-engineering-pi/learnings-researcher.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 | $0.00037 | $0.02520 |
| Opus 5.5 | $0.00015 | $0.01008 |
| Sonnet 5.5 | $0.00007 | $0.00504 |
| Haiku 4.5 | $0.00004 | $0.00252 |
Grade A, and why
learnings-researcher 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 — 264 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an expert institutional knowledge researcher specializing in efficiently surfacing relevant documented solutions from the team's knowledge base. Your mission is to find and distill applicable learnings before new work begins, preventing repeated mistakes and leveraging proven patterns.
Search Strategy (Grep-First Filtering)
The docs/solutions/ directory contains documented solutions with YAML frontmatter. When there may be hundreds of files, use this efficient strategy that minimizes tool calls:
Step 1: Extract Keywords from Feature Description
From the feature/task description, identify:
- Module names: e.g., "BriefSystem", "EmailProcessing", "payments"
- Technical terms: e.g., "N+1", "caching", "authentication"
- Problem indicators: e.g., "slow", "error", "timeout", "memory"
- Component types: e.g., "model", "controller", "job", "api"
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 · 264 lines · 37 tokens per session scan A fcd8bb5b6172
learnings-researcher is a skill published in the GitHub repository gvkhosla/compound-engineering-pi (52 stars, last pushed 15d ago), licensed MIT. It adds 37 tokens to every session and 2,520 once invoked, about $0.0001 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.
Other skills, from other repositories
pi-package-sandbox-test
Use when verifying that published Pi packages install and load for normal users, including pi.dev package compatibility checks, release validation, Daytona sandbox tests, and package installability audits.
pi-primitive-check
Use when evaluating proposed Pi customisation work against built-in Pi primitives before implementation, especially extensions, packages, slash commands, and workflow ideas.
pi-observability-local-dev
Use when developing or reviewing packages/pi-observability dashboard/server changes locally, especially rebuilding dist, restarting the 43190 server, validating UI behavior, or keeping the local dashboard in sync with source edits.
review-harness
Use when reviewing implementation work that ran through a /tmp Pi task harness. Checks contract drift, unsafe shortcuts, validation evidence, and status honesty.
pi
Use when needing a minimal, extensible terminal AI coding agent harness in TypeScript with plugin architecture. Pi: minimalist terminal AI coding agent emphasizing simplicity and composability.
execute-harness
Use when running an existing /tmp Pi task harness. Executes inside the active contract, records status, respects enforcement, and loops through validation.