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/gridaco/nothing/docs-wgnpx skills add gridaco/nothing --skill docs-wggit clone --depth 1 https://github.com/gridaco/nothingWhat 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 | $0.00150 | $0.03146 |
| Opus 5 | $0.00075 | $0.01573 |
| Sonnet 5 | $0.00030 | $0.00629 |
| Haiku 4.5 | $0.00015 | $0.00315 |
Grade A, and why
docs-wg 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 2d 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 — 228 lines — stays where its author put it; the contents beside it link to each section on GitHub.
WG docs
Working-group docs are where Grida reasons about a problem before and above any one implementation. A good WG doc could be handed to someone rebuilding the feature in a different language, on a different stack, in a different decade, and still be the right starting point. That is the bar.
The reason WG docs are code-agnostic is not stylistic. Code moves; a file path or a function name is stale within months, and a doc anchored to it rots into a lie. A doc anchored to the domain — the problem, the spec, the why — stays true as long as the problem does. You are writing the thing that outlives the code.
This skill is the doctrine. Operational mechanics (frontmatter,
format: md, draft/unlisted/doc_tasks, the sync model) live in
docs/AGENTS.md — read it once. For reading
the WG tree before you edit, use grounding.
The two genres
A WG doc is almost always one of these. Name which before you draft — they have different shapes.
1. RFC / RFD — spec
A specification of what a feature or system is and why it is that way. Spec-rich. It defines vocabulary, states constraints and invariants, and argues the design tradeoffs. It reads like a standards document, not like a code comment.
- A model, not an explanation. The strongest specs are models — a canonical vocabulary, a small generating rule or set of invariants, contract tables, and conformance clauses — the kind of thing a second implementer runs in their head. A doc that explains the code has the arrow backwards: the code conforms to the spec, never the reverse. Prose justifies the model; it does not substitute for it.
- Covers why and what. The motivation, the requirements, the model, the chosen design and the alternatives rejected (and why).
- No code-level implementation detail. Describe the behavior and the contract, not the functions that will realize them. If you find yourself naming a struct or a file, you have dropped from spec altitude into implementation — climb back up.
- Language- and stack-agnostic. Express the model in terms a second implementer could honor, not in terms of the current one.
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.
- 2d ago First seen · 228 lines · 150 tokens per session scan A a2fb0c2168fa
docs-wg is a skill published in the GitHub repository gridaco/nothing (43 stars, last pushed 2d ago), licensed Apache-2.0. It adds 150 tokens to every session and 3,146 once invoked, about $0.0007 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
freya
Freya Rust GUI framework best practices, patterns, and conventions. Use when writing Freya components, hooks, elements, or working on a Freya project.
docs-svg-kit
Author SVG figures for Grida docs — diff-able, version-controlled vector diagrams embedded in doc pages instead of screenshots. Provides reusable primitives (selection chrome, size badges, anchor pins, resize cursors, click ripples), color/typography tokens, a starter template, and finished examples to crib from.…
editor-perf
Guides performance investigation, benchmarking, and optimization of the Grida Canvas web editor (TypeScript reducer, Immer, React hooks). Use when profiling reducer dispatch cost, diagnosing slow interactions (drag, resize, color change), writing or running editor benchmarks, instrumenting with PerfObserver, or…
sdk-seam
Discipline for the seam between two SDKs (or two sides of one contract) that the same hand writes. The failure mode: "we own both sides" produces dirty contracts no foreign reviewer would accept. The exercise: pretend the other side is FFI, IPC, or a network protocol you cannot rewrite. Spawn an adversarial subagent…
agent-system
Grida AI agent system work: @grida/daemon (DaemonServer, loopback HTTP perimeter, files/workspaces, secrets store, daemon discovery) and @grida/agent (the agent tenant: sessions, providers/BYOK, runtime/tool execution, skills discovery, prompts, tiers, sandbox hosts). Use for packages/grida-daemon/…
ai-models
Research, compare, and update AI model configurations. Covers text model tiers, image and video generation models, image tool models, pricing data sourcing, and provider-cost metering against prepaid org credit. Use when bumping model versions, adding new models, updating pricing, or auditing model specs against…