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 agentmods add skills/noemuch/bridge/learning-from-correctionsnpx skills add noemuch/bridge --skill learning-from-correctionsgit clone --depth 1 https://github.com/noemuch/bridgeWrote 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/noemuch/bridge/learning-from-corrections)<a href="https://agentmods.dev/skills/noemuch/bridge/learning-from-corrections"><img src="https://agentmods.dev/badge/skills/noemuch/bridge/learning-from-corrections.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 | $0.00092 | $0.02467 |
| Opus 5 | $0.00046 | $0.01234 |
| Sonnet 5 | $0.00018 | $0.00493 |
| Haiku 4.5 | $0.00009 | $0.00247 |
Grade A, and why
learning-from-corrections 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 5d 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 — 260 lines — stays where its author put it; the contents beside it link to each section on GitHub.
{{ACTIVE_RULES}}
Learning From Corrections
Overview
Closes the feedback loop from manual Figma edits back into Bridge's knowledge base. Diffs the live Figma state against the saved snapshot, classifies each correction as a LEARNING (DS-compliant → persisted) or a FLAG (hardcoded → surfaced), updates learnings.json, and auto-patches the active recipe when eligible.
When to Use
Invoke when the user:
- says "I adjusted it", "I fixed it in Figma", "fix", "correct", or "learn from what I changed"
- has an active CSpec in
specs/active/with a snapshot
Do NOT use if:
- there is no active CSpec — the user should
makefirst (usegenerating-figma-design) - the user wants to start fresh — use
generating-figma-designwith a new description - the user wants to ship — use
shipping-and-archiving
Procedure
Before starting, load:
references/transport-adapter.md(repo-root) — for Figma state re-readreferences/compiler-reference.md(repo-root) — for scene graph recompile (if re-executing after fix)
Prerequisites
- Active CSpec in
specs/active/(abort if missing: "No active CSpec. Run:make <description>") - Snapshot file exists at
specs/active/{name}-snapshot.json(abort if missing: "No snapshot found. The design must have been generated withmake. Runmakefirst.") - Figma MCP transport available (see
references/transport-adapter.md(repo-root) Section F)
1. Load artifacts
- Read the active CSpec from
specs/active/{name}.cspec.yaml - Read the snapshot from
specs/active/{name}-snapshot.json - Read existing learnings from
knowledge-base/learnings.json(create empty structure if file doesn't exist) - Load
knowledge-base/registries/variables.jsonfor token resolution
2. Re-extract current Figma state
Run a node tree extraction script via Plugin API execution, using the rootNodeId and fileKey from the snapshot's meta.
Console transport:
figma_execute({
code: "return (async function() { ... extraction script with rootNodeId ... })();"
})
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.
- 5d ago First seen · 260 lines · 92 tokens per session scan A 689a10729f12
learning-from-corrections is a skill published in the GitHub repository noemuch/bridge (156 stars, last pushed 3mo ago), licensed MIT. It adds 92 tokens to every session and 2,467 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 2026-08-30.
Other skills, from other repositories
work-with-design-systems
Inspect, build, or extend Figma design systems — and optionally sync them to code. Two modes in one skill: inspect mode (read-only audits with WCAG checks, component scoring, detached instance detection, handoff docs) and build mode (creating components with variable bindings, slot-based composition, structured…
create-anatomy
Generate a visual anatomy annotation in Figma showing numbered markers on a component instance with an attribute table. Use when the user mentions "anatomy", "anatomy annotation", "component anatomy", "create anatomy", or wants to annotate a component's structural elements.
create-property
Generate a visual property annotation in Figma showing each configurable property axis with component instance previews. Use when the user mentions "property", "properties", "property annotation", "create property", or wants to document a component's configurable properties visually.
create-component-md
Generate a canonical JSON contract and a self-contained implementation Markdown specification for a Figma component covering API, structure, color, and screen-reader behavior. Reads a base.json produced by the uSpec Extract plugin, runs four read-only interpretation skills in parallel, reconciles their outputs, and…
create-structure
Generate structure specifications documenting component dimensions, spacing, padding, and how values change across density, size, and shape variants. Use when the user mentions "structure", "structure spec", "dimensions", "spacing", "density", "sizing", or wants to document a component's dimensional properties.
create-color
Generate color annotation specifications mapping UI elements to design tokens. Use when the user mentions "color", "color annotation", "color spec", "tokens", "design tokens", or wants to document which color tokens a component uses.