Ski entity file builder
Skill luisdomarco/AiAgentArchitect/.agents/skills/ski-entity-file-builder
AI Agent Architect: A comprehensive framework for designing, building, and exporting agentic workflows. Seamlessly transition from initial concept to production-ready agents equipped with custom commands, specialized skills, knowledge bases and rules.
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Generates complete, correctly formatted instruction files for all 10 entity types (Workflow, Agent, Skill, Command, Rule, Knowledge-base, Resources, Script, Hook) per assigned intricacy level. Use in Step 3 to materialize each entity from the architectural blueprint as a deployable file.
SKILL.md
6.4 KB, as published. Nobody here has run it
Entity File Builder Skill
Generates the complete content of instruction files for each entity type, adapting the depth to the assigned intricacy level and respecting all formatting conventions.
Input / Output
Input:
- Entity type:
workflow | agent-specialist | agent-supervisor | skill | command | rule | knowledge-base | script | hook - Intricacy level:
simple | medium | complex - Entity data from handoff JSON (name, description, function, input, output, relationships)
- List of entities already created in the session (for correct cross-references)
Output:
- Complete
.mdfile with YAML frontmatter and Markdown body, ready to download
Procedure
1. Pre-generation: mandatory verifications
Before writing the file, verify:
- The name follows the kebab-case convention with the correct prefix for its type.
- The frontmatter description does not exceed 250 characters.
- Cross-reference paths use the correct relative format.
- The intricacy level determines the content density (see section 4).
- The expected size and density: if the projected content approaches or exceeds the recommended character limit for the entity type (<6000 Workflow/KB, <3000 Agent/Rule, <1500 Skill/Command), prepare to partition it by creating documents in the
/resourcesdirectory and referencing them.
2. Naming conventions by type
| Type | Prefix | Example |
|---|---|---|
| Workflow | wor- | wor-customer-onboarding.md |
| Agent Specialist | age-spe- | age-spe-email-classifier.md |
| Agent Supervisor | age-sup- | age-sup-output-validator.md |
| Skill | ski- | ski-format-output/SKILL.md |
| Command | com- | com-quick-translate.md |
| Rule | rul- | rul-output-standards.md |
| Knowledge-base | kno- | kno-brand-guidelines.md |
| Resources | res- | res-security-policies.md |
| Script | scp- | scp-lint-check.sh |
| Hook | hok- | hok-validate-on-save.md |
3. Templates by entity type
Templates are split by entity category to minimize context load:
- Behavioral entities (
wor-,age-spe-,age-sup-,com-): read../../resources/res-entity-templates-behavioral.md - Support entities (
ski-,rul-,kno-,res-,scp-,hok-): read../../resources/res-entity-templates-support.md
Extract the structure for the requested entity type and fill it dynamically per the assigned intricacy level.
4. Intricacy levels and cross-reference rules
Full specifications for all three intricacy levels (simple, medium, complex), cross-reference path conventions, consistency rules, content partitioning, and pre-validation checklist:
../../resources/res-entity-builder-protocol.md
Platform output: This skill generates GA (
.agents/) entities only. Platform-specific output (CC, Codex) is handled byski-output-claude-codeandski-output-codexrespectively. Skills use theski-[name]/SKILL.mdsubdirectory structure on all platforms — never create flatski-name.mdfiles.
5. Content Structuring and Partitioning (/resources)
If when planning the intricacy level (especially for complex) you anticipate a very extensive entity or one that will exceed the recommended limit:
- Identify dense blocks that could be externalized (e.g. very long prompts, extensive categorization tables, few-shot examples, detailed style policies or guides).
- Determine which support files to create in the
./resources/directory to host that raw information. - In the main entity, make a direct reference to the support files structuring the information as a relational system. E.g.
See detailed policies in [Security Policies](./resources/res-security-policies.md).
6. Pre-presentation validation
After generating the entity content and before returning it, run this automated checklist:
- Frontmatter:
nameanddescriptionare present;description≤ 250 chars. - Cross-references: Each path in Skills/KB/Rules tables points to an entity that exists or is planned in
creation_order. - Character count: If the entity exceeds the recommended limit for its type, flag it with a suggestion to partition into
resources/. - Template conformance: All required sections for the entity type are present and non-empty.
- Naming: Correct prefix for the entity type and kebab-case format.
Emit a summary line at the end of the generated entity:
Pre-validation: ✅ frontmatter | ✅ cross-refs | ✅ size (2847/3000) | ✅ sections | ✅ naming
If any check fails, use ⚠️ and describe the issue. Do not suppress failures.
7. Universal compliance requirement for generated agents
Universal requirement (all intricacy levels): Every generated agent (type age-spe-* or age-sup-*) MUST include in its Execution Protocol:
"Before presenting your output, emit a
<sys-eval>block perrul-strict-compliance."
Every agent's Related rules table MUST include rul-strict-compliance. This ensures all generated systems produce traceable outputs.
Examples
Example — Generation of Agent Specialist at simple level
Input:
{
"type": "agent-specialist",
"name": "age-spe-email-classifier",
"function": "Classify incoming emails into predefined categories",
"intricacy_level": "simple"
}
Expected output: Agent with Goals (2), Tasks (4), linear Execution Protocol (5-6 steps), Specific Rules (3), without Skills or KB if not needed.
Error Handling
- Name does not follow convention: Automatically correct and notify the user.
- Description exceeds 250 characters: Summarize while maintaining the essential meaning.
- Reference to entity not yet created: Include the reference with the correct path and indicate in a comment that entity will be created later.
- Inconsistency detected with the Blueprint: Pause, notify the user, and ask for clarification before continuing.