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 adonai-labs/agent-runway --skill learninggit clone --depth 1 https://github.com/adonai-labs/agent-runwayWrote 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/adonai-labs/agent-runway/learning)<a href="https://agentmods.dev/skills/adonai-labs/agent-runway/learning"><img src="https://agentmods.dev/badge/skills/adonai-labs/agent-runway/learning.svg" alt="Measured on agentmods" 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 | $0.00058 | $0.00782 |
| Opus 5 | $0.00029 | $0.00391 |
| Sonnet 5 | $0.00012 | $0.00156 |
| Haiku 4.5 | $0.00006 | $0.00078 |
Grade A, and why
learning 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 7d 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 — 98 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Learning
Invoke Skill
@learning <lesson or observation>
Examples:
@learning we do not use generic repositories in this service@learning tests must use Testcontainers because SQLite hides provider issues@learning auth changes need a manual permission matrix check
What this skill does
Turns a useful lesson into a concise memory entry under .agent-runway/memory/.
Use it for reusable project knowledge, not for run history. If the information only explains what happened in the current session, use @checkpoint instead.
Workflow
1. Classify the lesson
Choose exactly one target file:
| Target | Use when |
|---|---|
.agent-runway/memory/project-decisions.md |
Architecture, product, API, schema, dependency, or team decision |
.agent-runway/memory/execution-memory.md |
Operational guardrail, validation step, setup issue, release/deploy lesson |
.agent-runway/memory/reasoning-memory.md |
A recommendation changed after trade-off analysis or contrarian evidence |
.agent-runway/memory/recurring-patterns.md |
Repeated implementation convention, naming, module, or workflow pattern |
.agent-runway/memory/common-failures.md |
Repeated bug class, test miss, migration issue, integration failure, or review finding |
.agent-runway/memory/testing-notes.md |
Test strategy, fixture, environment, or coverage lesson |
.agent-runway/memory/review-findings.md |
Review pattern likely to appear again |
.agent-runway/memory/ticket-quality-notes.md |
Ticket/spec quality issue or acceptance criteria lesson |
If more than one file could fit, pick the narrowest reusable target.
2. Validate it is worth saving
Save only if the lesson is:
- durable: likely to matter again
- specific: tied to this project or stack
- actionable: changes future behavior
- non-sensitive: no secrets, credentials, customer data, or private incident detail
If it is too vague, ask one clarifying question. If it is only session state, recommend @checkpoint.
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.
- 7d ago First seen · 98 lines · 58 tokens per session scan A 32a735256218
learning is a skill published in the GitHub repository adonai-labs/agent-runway (2 stars, last pushed 17d ago), licensed MIT. It adds 58 tokens to every session and 782 once invoked, about $0.0003 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 2026-08-31.
Other skills, from other repositories
mindos
MindOS: local knowledge assistant & shared KB. Keeps decisions, notes, SOPs, debugging lessons, research findings, preferences across sessions/agents. Core: save notes, search KB, organize files, run workflows, review, append CSV, hand off context, distill lessons. NOT for app source or paths outside KB. Triggers…
init-workspace-documentation
Skill "init-workspace-documentation" from griddynamics/rosetta, covering agent memory.md, agent memory, preventive rules, what worked and what failed.
tour
Interactive onboarding walkthrough for a new engineer. Use for "give me a tour", "onboard me", "walk me through the codebase".
spec-harness-build
Run the SDD pipeline over tasks.md: implement → test → VERIFY → review, one task at a time, under the ratchet. Use when Malik says 'build it', 'run the pipeline', 'implement the tasks', or 'ship this feature'. Each task gated by the separate verifier; lessons harvested by learn.
fec-image-generation
A workflow for creating or editing images and diagrams, from posters and product mockups to academic graphics, illustrations, and system maps. For text-heavy technical diagrams, it can use editable sources such as Mermaid, SVG, HTML, or canvas before exporting an image.
totem-compiled-rules
Compiled architectural rules and lessons from the Totem knowledge base. Load this when reviewing code for pattern violations or architectural drift.