com um clique
writing-skills
Guidelines for creating, reviewing, and improving agent skills.
Instalar com Codex ou Claude Copie este prompt, cole no Codex, Claude ou outro assistente e deixe que ele revise a página da skill e instale para você.
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Guidelines for creating, reviewing, and improving agent skills.
Instalar com Codex ou Claude Copie este prompt, cole no Codex, Claude ou outro assistente e deixe que ele revise a página da skill e instale para você.
Baseado na classificação ocupacional SOC
| name | writing-skills |
| description | Guidelines for creating, reviewing, and improving agent skills. |
This skill governs how agent skills are authored and audited. It contains two paths: a Creation path for new skills, and a Review path for existing skills.
When creating or editing skills, follow the Inlined Expertise philosophy:
references/.references/ for explanations, history, or large templates.A skill's directory layout follows the agentskills.io standard:
<skill-name>/
├── SKILL.md # Entry point + Inlined Expertise (SOPs)
├── references/ # Detailed docs, templates, deep-dives
├── scripts/ # Optional automation tools
└── assets/ # Static files
The x/tool/skills/ loader serves both the canonical SKILL.md and any
file under references/ through the read_skill tool. The LLM reads
SKILL.md, follows a markdown link like [Example](./references/example.md),
and resolves it to read_skill(name="<skill>", path="references/example.md").
The same abstraction works for filesystem, embedded, and any future
remote discoverer — references are never loaded through a generic
read_file tool.
Example of Inlined Expertise (in SKILL.md):
"Run
go test -race ./...to verify changes." (Direct instruction)
Example of Reference link (in SKILL.md):
"See Example Reference for an example." (Deep dive)
Example of a tool call the LLM makes to follow that link:
read_skill(name="<skill>", path="references/example.md")
Ask 1–3 high-value questions before drafting. Probe intent, scope, target audience, prior attempts, and related skills. Avoid open-ended questions that invite the user to dump context; ask for the specific decision-blocking information.
Propose a hypothesis about scope, name, and shape. Give the user something concrete to disagree with. Frame as a starting point, not a finished design.
Iterate: propose → correct → revise. Show what changed between iterations so the user can audit the reasoning. Each iteration should narrow scope or sharpen wording, not expand.
Land on a 1–2 sentence problem statement, explicit scope boundaries, and at least one acknowledged constraint. State the proposed skill name, target repo, and parent directory.
Ask the user: "Want me to draft the SKILL.md?" Do not write the file until they confirm. When they do, draft to the agreed location and present the result.
When asked to review, audit, check, or improve an existing SKILL.md, run the gates below against it. Output enumerated findings only; do not render pass/fail verdicts. The user decides what to act on.
name is lowercase-hyphenated and matches the parent directory name exactly.description is a single declarative sentence stating what the skill does and when to use it.name and description — no license, metadata, compatibility, or allowed-tools.references/.# <Capitalized Skill Name>.A skill is complete when:
SKILL.md — critical instructions are not buried in references/.Codifies the principle of centrality-weighted reasonability for Go code in the ore repository. Central packages (many dependents, high change impact) must be radically simple, while peripheral packages (few dependents, low change frequency) can carry more internal complexity provided they are self-contained. The skill guides agents to keep code simple in a contextual way: simplicity is risk management, not a moral virtue.
Implements a new ore I/O conduit package under x/conduit/<name>/ using the functional-options constructor pattern, exported Descriptor for discovery, and blocking Start(ctx) lifecycle. Dumb pipe that translates external system events (HTTP, TUI, chat bot, webhook) into ore session events via junk.Manager, subscribes to broadcast FanOut output streams, and routes text/reasoning/image artifacts back to external systems. Compatible with the broadcast multi-conduit model. Does NOT handle cognitive orchestration, provider invocation, or turn-loop management.
How to create and label GitHub issues for the ore repository. Load this skill whenever you need to open a new issue.
Guidelines for Go development, testing, and tooling.
Implements a new ore I/O conduit package.