What is capture-learning-tools?

An engineering learning workflow that turns technical problems and repeated agent mistakes into improvements in a software project. Improvements can include tests, CI checks, scripts, templates, documentation, or architecture decisions.

Use it after bugs, CI failures, code reviews, or repeated mistakes to decide what should be automated, documented, tested, or added to agent instructions.

It helps prevent the same bug, review issue, or failed check from happening again by putting the lesson into the repository.

How The-Vibe-Company/companion configures Claude Code

About the project

Companion is a self-hosted, multi-tenant hub for managing personal and organizational SKILL.md libraries used by coding agents. It is for organizations that need to store, validate, version, share, install, update, and synchronize agent skills, with optional named companions that have persistent workspaces and chats. The catalogue skills, agents, and instructions are resources managed or used within this workflow.

The-Vibe-Company/companion · 2,401 stars · on GitHub · thecompanion.sh

Reuse

Borrowing it

Nothing to install: this file belongs to The-Vibe-Company/companion. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file

curl -O https://raw.githubusercontent.com/The-Vibe-Company/companion/main/.agents/skills/capture-learning-tools/SKILL.md

Clone the repo

git clone --depth 1 https://github.com/The-Vibe-Company/companion

Made for: Claude Code.

Wrote 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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/the-vibe-company/companion/capture-learning-tools/github.svg)](https://agentmods.dev/skills/the-vibe-company/companion/capture-learning-tools)

Your own site

<a href="https://agentmods.dev/skills/the-vibe-company/companion/capture-learning-tools"><img src="https://agentmods.dev/badge/skills/the-vibe-company/companion/capture-learning-tools/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.

Your own site · 80×15

<a href="https://agentmods.dev/skills/the-vibe-company/companion/capture-learning-tools"><img src="https://agentmods.dev/badge/skills/the-vibe-company/companion/capture-learning-tools.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 109 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 1,601 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits

NVIDIA SkillSpector pass 7 Sept 2026

How audits are shown

Origin original No closer match found in the catalogue.

Token cost

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	$0.00109	$0.01601
Opus 5	$0.00055	$0.00800
Sonnet 5	$0.00022	$0.00320
Haiku 4.5	$0.00011	$0.00160

Measured 9d ago against content hash a15b00a0e484, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

capture-learning-tools 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 9d ago.

The scan reads SKILL.md. This mod also ships 3 executable files (scripts/classify_learning.py, scripts/inspect_ci_surface.py, scripts/inspect_project_guidance.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

.agents/skills/capture-learning-tools/SKILL.md · 153 lines

How it starts

The opening of the file, as written. The whole thing — 153 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Engineering Learning Loop

This skill is the prevention layer after technical work. It analyzes the conversation and the repository, then promotes useful lessons into the project itself: agent instructions, tests, CI, scripts, templates, docs, or architecture decisions.

The project is the source of truth. Do not depend on private memory systems, personal vaults, or one agent host. A good outcome makes the repository easier for the next human or agent to work in.

Protected Invariants

Propose before editing. Apply changes only when the user explicitly asks or the task clearly requests implementation.
Prefer enforceable safeguards over prose. If a test, script, or CI check can catch the issue reliably, recommend that before adding a reminder.
Keep non-technical users oriented. Start with a plain-English verdict before technical details.
Keep instructions portable. Do not hard-code private paths, organizations, account names, secrets, or tool-only assumptions.
Do not turn every mistake into a rule. Some learnings are one-off judgment calls and should be left manual.
Never stage, commit, push, create a PR, or change billing-sensitive CI behavior unless explicitly asked.

Reference Routing

Read only what the task needs:

references/conversation-analysis.md when extracting lessons from a conversation, transcript, review, bug, or user correction.
references/promotion-matrix.md for deciding whether the lesson belongs in instructions, tests, CI, scripts, docs, ADRs, or nowhere.
references/agent-instructions.md when changing or proposing AGENTS.md, CLAUDE.md, .claude/rules/, Cursor rules, or other agent guidance.
references/ci-policy.md before recommending CI, especially for private repositories, paid runners, long checks, or open-source projects.
references/testing-policy.md before recommending regression tests or coverage changes.
references/project-memory.md when the repository needs a durable place for decisions, runbooks, templates, or recurring project knowledge.
references/cross-agent-linking.md when multiple agent hosts need the same instructions.
references/non-technical-mode.md when the user is not clearly technical or asks for a simple explanation.
references/examples.md for concrete before/after patterns.

Read the full file on GitHub · 153 lines

Files

What ships with it

14 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

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.

9d ago First seen · 153 lines · 109 tokens per session scan A a15b00a0e484

Subscribe to this mod's changes

capture-learning-tools is a skill published in the GitHub repository The-Vibe-Company/companion (2,401 stars, last pushed 3d ago), licensed MIT. It adds 109 tokens to every session and 1,601 once invoked, about $0.0005 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 2026-09-02.

Testing

research-engineer

An uncompromising Academic Research Engineer. Operates with absolute scientific rigor, objective criticism, and zero flair. Focuses on theoretical correctness, formal verification, and optimal implementation across any required technology.

davila7/claude-code-templates · 43 tokens

tika-eval-compare

Compare extracts from two Tika builds over a corpus to detect regressions in content, encoding, exceptions, and embedded-document handling. Use for "compare before/after extracts", "eval this change against the corpus".

apache/tika · 50 tokens

neuron-evaluation-engineer

Create and run AI evaluations with datasets, assertions, and output drivers in Neuron AI. Use this skill whenever the user mentions evaluation, testing AI systems, creating evaluators, dataset-driven testing, assertion-based validation, or wants to measure AI system performance. Also trigger for tasks involving…

neuron-core/neuron-ai · 77 tokens

companion: Skill for Claude Code