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production-agent-skill-lifecycle

Guides agents through designing, reviewing, and maintaining production-grade agent skills with trigger-focused frontmatter, behavioral workflows, anti-rationalization, and evidence gates. Use when creating or upgrading SEOSONA skills, importing external skill packs, or auditing whether a skill changes agent behavior under pressure.

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LongLeo287/SEOSONA-OS
Última atividade na origem
4 de agosto de 2026 às 05:01
Idioma detectado do SKILL.md
inglês
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2
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SKILL.md
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name
production_agent_skill_lifecycle
description
Guides agents through designing, reviewing, and maintaining production-grade agent skills with trigger-focused frontmatter, behavioral workflows, anti-rationalization, and evidence gates. Use when creating or upgrading SEOSONA skills, importing external skill packs, or auditing whether a skill changes agent behavior under pressure.
# Production Agent Skill Lifecycle ## Overview Use this skill when a SEOSONA capability should become a reusable agent skill rather than a one-off note. The goal is to encode a repeatable workflow that agents can discover, execute, verify, and improve. ## When To Use - Creating a new skill from external research. - Refactoring a vague knowledge note into an operational workflow. - Auditing a skill that reads like documentation but does not change behavior. - Importing skill packs from another agent ecosystem. Do not use this for simple static reference notes. Use `2_KNOWLEDGE/raw_data/` for passive knowledge that has no repeatable workflow. ## Workflow 1. Define the behavioral trigger. - The frontmatter description must say what the skill does and when to use it. - Avoid process summaries in the description; the agent must still read the full skill. 2. Write the operating loop. - Use phases or numbered steps. - Make every step observable. - Name stop conditions and handoff boundaries. 3. Add anti-rationalization. - List excuses that agents use to skip work. - Pair each excuse with the operational reason it is unsafe. 4. Add red flags. - Describe visible signs of drift, such as skipping verification, inventing source facts, or expanding scope without a plan update. 5. Add verification. - Require command output, source links, screenshots, tests, or generated artifacts. - "Looks good" is not evidence. 6. Keep progressive disclosure. - Keep `SKILL.md` focused. - Move long reference material into `references/`. - Add scripts only when they are actually run by the workflow. 7. Register and validate. - Rebuild the capability graph/router after adding skills. - Run the smallest relevant validation gate. ## Skill Anatomy Required: - `SKILL.md` - YAML frontmatter with `name` and `description` - A clear workflow and verification section Recommended: - `When To Use` - `Workflow` - `Common Rationalizations` - `Red Flags` - `Verification` - `References` Optional: - `references/` for long checklists or examples - `scripts/` for repeatable helper commands - `templates/` for generated artifacts ## Common Rationalizations | Rationalization | Reality | | --- | --- | | "This is obvious; the skill can be short." | Obvious steps are the first steps agents skip under pressure. | | "The README explains it." | A README informs; a skill changes execution behavior. | | "Verification can be done later." | A skill without exit evidence is a suggestion, not an operating contract. | | "More context is always better." | Overloaded skills reduce discoverability and increase drift. | ## Red Flags - The description says only a topic, not a trigger. - The body is mostly background prose. - There is no exit checklist. - The workflow asks the user for permission when local context can answer safely. - The skill duplicates another skill instead of referencing it. ## Verification After creating or upgrading a skill, confirm: - [ ] The description includes both what and when. - [ ] The workflow has concrete steps. - [ ] The skill has evidence-based verification. - [ ] No absolute local paths were written. - [ ] Capability validation or router rebuild was run.
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