# Sk Doc

> Markdown and OpenCode component specialist: doc quality, content optimization, component scaffolds, install guides, playbooks.

- **Type:** Skill
- **Install:** `agentstack add skill-michelkerkmeester-opencode-skilled-agent-loops-with-spec-kit-memory-sk-doc`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [MichelKerkmeester](https://agentstack.voostack.com/s/michelkerkmeester)
- **Installs:** 0
- **Category:** [Content & Media](https://agentstack.voostack.com/c/content-and-media)
- **Latest version:** 0.1.0
- **License:** MIT
- **Upstream author:** [MichelKerkmeester](https://github.com/MichelKerkmeester)
- **Source:** https://github.com/MichelKerkmeester/opencode--skilled-agent-loops-with-spec-kit-memory/tree/main/.opencode/skills/sk-doc

## Install

```sh
agentstack add skill-michelkerkmeester-opencode-skilled-agent-loops-with-spec-kit-memory-sk-doc
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

# Documentation Creation Specialist - Unified Markdown & Component Management

Unified specialist providing: (1) Document quality pipeline with structure enforcement and content optimization, (2) OpenCode component creation (skills, agents, commands) with scaffolding, validation and packaging, (3) ASCII flowchart creation for visualizing workflows, (4) Install guide creation for setup documentation and (5) Feature catalog and manual testing playbook creation for inventory and validation packages.

**Core Principle**: Structure first, then content, then quality.

**Architecture**: Scripts handle deterministic parsing/metrics. AI handles quality judgment and recommendations.

## 1. WHEN TO USE

### Use Case: Document Quality Management

Enforce markdown structure, optimize content for AI assistants, validate quality through script-assisted AI analysis.

**README Creation** - Use `readme_template.md` + `readme_creation.md` when:
- Creating new README for any folder or project
- User requests "create a README", "add documentation", "write a README"
- Folder needs comprehensive documentation
- Workflow: [readme_creation.md](./references/readme_creation.md) | Template: [readme_template.md](./assets/readme/readme_template.md)

**Skill README Creation** - Use `skill_readme_template.md` when:
- Creating or refreshing `.opencode/skills/[skill-name]/README.md`
- A skill README needs human-facing purpose, quick start, structure, examples, troubleshooting, FAQ or related-resource navigation
- Template: [skill_readme_template.md](./assets/skill/skill_readme_template.md)

**Frontmatter Validation** - Use `frontmatter_templates.md` when:
- Validating YAML frontmatter in any document
- Checking required fields for document types
- Fixing frontmatter syntax errors

**Changelog & Release Notes** - Use `changelog_template.md` when:
- Authoring a global component changelog at `.opencode/changelog/{NN--component}/v{VERSION}.md`
- Composing GitHub release notes that mirror the changelog body
- Choosing between compact (under 10 changes) and expanded (10+ changes or major) formats
- Template: [changelog_template.md](./assets/changelog_template.md). Used by `/create:changelog` (auto + confirm). Nested packet-local changelogs use the spec-kit templates at `.opencode/skills/system-spec-kit/templates/changelog/` instead.

**Validation Workflow** - Apply after Write/Edit operations:
- Auto-correct filename violations (ALL CAPS to lowercase, hyphens to underscores)
- Fix safe violations (separators, H2 case)
- Check critical violations (missing frontmatter, wrong section order)

**Manual Optimization** - Run when:
- README needs optimization for AI assistants
- Creating critical documentation (specs, knowledge, skills)
- Pre-release quality checks
- Generating llms.txt for LLM navigation

### Use Case: OpenCode Component Creation

Create and manage OpenCode components (skills, agents, commands). Each component type has templates and validation with quality standards.

**Component Types:**
- **Skills** (.opencode/skills/) - Knowledge bundles with workflows → [skill_creation.md](./references/skill_creation.md)
- **Agents** (.opencode/agents/) - AI personas with tool permissions → [agent_creation.md](./references/agent_creation.md)
- **Commands** (.opencode/commands/) - Slash commands for user invocation → [command_template.md](./assets/command/command_template.md)

For larger skills, split deep content into focused reference files and keep concise navigation in `SKILL.md` or `README.md`. When a skill has both cross-cutting standards and document-family guides, prefer `references/global/` for shared rules and the `references/` root for creation-specific workflows.

Start with: [skill_creation.md](./references/skill_creation.md), then [overview.md](./references/skill_creation/overview.md) for skill structure
Primary templates:
- [skill_md_template.md](./assets/skill/skill_md_template.md)
- [skill_readme_template.md](./assets/skill/skill_readme_template.md)
- [skill_reference_template.md](./assets/skill/skill_reference_template.md)
- [skill_asset_template.md](./assets/skill/skill_asset_template.md)

**Use when**:
- User requests skill creation ("create a skill", "make a new skill")
- User requests agent creation ("create an agent", "make a new agent")
- User requests command creation ("create a command", "add a slash command")
- Scaffolding component structure
- Validating component quality
- Packaging skill for distribution

**Skill Process (6 steps)**: Understanding (examples) → Planning (resources) → Initialization (`init_skill.py`) → Editing (populate) → Packaging (`package_skill.py`) → Iteration (test/improve)

**Agent Process**: Load `agent_creation.md` and `agent_template.md` → Define frontmatter (mode, permissions) → Create sections (workflow, capabilities, anti-patterns) → Validate → Test

**Command Process**: Load `command_template.md` → Define frontmatter (name, description) → Create execution logic → Add to command registry → Test

### Use Case: Flowchart Creation

Create ASCII flowcharts for visualizing workflows, user journeys and decision trees.

For styled HTML visuals (interactive diagrams, dashboard pages, or polished data-table renders), use a dedicated HTML workflow instead of forcing ASCII or markdown flowcharts.

**Use when**:
- Documenting multi-step processes with branching
- Creating decision trees with multiple outcomes
- Showing parallel execution with sync points
- Visualizing approval gates and revision cycles

**See**: [assets/flowcharts/](./assets/flowcharts/)

### Use Case: Install Guide Creation

Create and validate installation documentation for MCP servers, plugins and tools using phase-based templates.

**Use when**:
- Creating documentation for MCP server installation
- Documenting plugin setup procedures
- Standardizing tool installation across platforms
- Need phase-based validation checkpoints

**5-Phase Process**: Overview → Prerequisites → Installation → Configuration → Verification

**See**: [install_guide_creation.md](./references/install_guide_creation.md)

### Use Case: Manual Testing Playbook Creation

Create manual testing playbooks with deterministic scenarios, structured evidence collection, and multi-agent execution planning.

**Manual Testing Playbook** - Use `testing_playbook/manual_testing_playbook_template.md` when:
- Creating manual testing scenarios for a skill
- Standardizing test evidence and verdict criteria
- Setting up multi-agent test execution planning

**Canonical Package**: Root `manual_testing_playbook.md` plus numbered category folders with one per-feature file per feature ID.

**See**:
- [manual_testing_playbook_creation.md](./references/manual_testing_playbook_creation.md)
- [manual_testing_playbook_template.md](./assets/testing_playbook/manual_testing_playbook_template.md)

### Use Case: Feature Catalog Creation

Create feature catalogs with a rooted feature inventory, numbered category sections, and per-feature reference files.

**Feature Catalog** - Use `assets/feature_catalog/feature_catalog_template.md` when:
- Creating a canonical current-state feature inventory for a skill or system
- Linking manual playbooks back to a stable feature reference
- Documenting current behavior with source-file anchors and stable slugs

**Canonical Package**: Root `FEATURE_CATALOG.md` plus numbered category folders with one per-feature file per catalog entry.

**See**:
- [feature_catalog_creation.md](./references/feature_catalog_creation.md)
- [feature_catalog_template.md](./assets/feature_catalog/feature_catalog_template.md)

### Use Case: Benchmark Folder Creation

Create skill-local `mcp_server/benchmarks/benchmark-/` folders that promote curated bake-off results from an originating spec packet into the consuming skill, where operators reading the MCP code can find the headline without leaving the skill tree.

**Benchmark Creation** - Use `benchmark_report_template.md` plus `source_template.md` when:
- An ADR or spec packet has just promoted a non-trivial default change (embedder swap, reranker change, retrieval policy) backed by measured evidence
- The originating spec packet has a stable headline plus replay commands and is worth surfacing inside the consuming skill
- A sibling skill already ships a `mcp_server/benchmarks/` folder and parity matters for operators moving between skills

**Canonical Package**: One `benchmark-/` folder per run, holding `benchmark_report.md` (ten-section curated narrative), `SOURCE.md` (wayfinding pointer back to the spec packet), `results.csv`, `*.jsonl` per-probe data, and optional sidecars (`runtime-measurements.md`, `risk-analysis-*.md`).

**See**:
- [benchmark_creation.md](./references/benchmark_creation.md)
- [benchmark_report_template.md](./assets/benchmark/benchmark_report_template.md)
- [source_template.md](./assets/benchmark/source_template.md)

### When NOT to Use (All Modes)

- Non-markdown files (only `.md` supported)
- Simple typo fixes (use Edit tool directly)
- Internal notes or drafts
- Auto-generated API docs
- Short 2-3 step processes (use bullet points)

---

## 2. SMART ROUTING

> Pattern: see [sk-doc smart-router resilience template](./assets/skill/skill_smart_router.md).

### Resource Domains

The router discovers markdown resources recursively from `references/` and `assets/` and then applies intent scoring from `RESOURCE_MAP`. Keep this section domain-focused rather than static file inventories.

- `references/global/` for documentation standards, validation rules, optimization guidance, voice rules, and shared execution workflows.
- `references/` root for document-family and component creation guides such as skill creation, agent creation, install guides, feature catalogs, and manual testing playbooks.
- `assets/readme/` for README and install-guide scaffolds; `assets/changelog_template.md`, `assets/frontmatter_templates.md`, and `assets/llmstxt_templates.md` at the assets/ root for cross-cutting templates.
- `assets/skill/` for skill creation templates, including `SKILL.md`, skill README, reference and asset scaffolds; `assets/agent_template.md` at the assets/ root and `assets/command/command_template.md` (with `assets/command/command_presentation_template.md`) for agent and command creation templates.
- `assets/feature_catalog/` and `assets/testing_playbook/` at the assets/ root for feature catalog and manual testing playbook package templates.
- `assets/benchmark/` for skill-local benchmark folder templates (`benchmark_report_template.md`, `source_template.md`).
- `assets/flowcharts/` for reusable ASCII flowchart patterns and diagram examples.

> **Cross-CLI consumption note** (per packets 071/072 stress-test data): when sk-doc is dispatched via an external CLI and the caller consumes the routing-trace output LITERALLY (e.g. attempts to `Read()` cited resource paths), prefer **cli-codex** (gpt-5.5/high/fast) — it scored 66.7% resource-accuracy vs cli-opencode 47.2% on the sk-doc router stress matrix. claude-opus-4.7 tends to hallucinate plausible-sounding paths that don't exist in this skill's filesystem; treat its routing trace as advisory and verify cited paths before reading. See the local router stress-test notes for the full data and hallucination finding.

### Resource Loading Levels

| Level       | When to Load             | Resources                   |
| ----------- | ------------------------ | --------------------------- |
| ALWAYS      | Every skill invocation   | Quick reference baseline    |
| CONDITIONAL | If intent signals match  | Mode-specific docs/templates|
| ON_DEMAND   | Only on explicit request | Extended standards/template |

### Smart Router Pseudocode

The authoritative routing logic for scoped loading, weighted intent scoring, and ambiguity handling.

- Pattern 1: Runtime Discovery - `discover_markdown_resources()` recursively scans `references/` and `assets/`.
- Pattern 2: Existence-Check Before Load - `load_if_available()` guards, checks `inventory`, and suppresses repeats with `seen`.
- Pattern 3: Extensible Routing Key - intent labels route to document families without static inventories.
- Pattern 4: Multi-Tier Graceful Fallback - `UNKNOWN_FALLBACK` requests disambiguation and missing families return a "no knowledge base" notice.

```python
from pathlib import Path

SKILL_ROOT = Path(__file__).resolve().parent
RESOURCE_BASES = (SKILL_ROOT / "references", SKILL_ROOT / "assets")
DEFAULT_RESOURCE = "references/global/quick_reference.md"

INTENT_SIGNALS = {
    "DOC_QUALITY": {"weight": 4, "keywords": ["dqi", "quality", "validate", "extract_structure"]},
    "OPTIMIZATION": {"weight": 3, "keywords": ["optimize", "llms.txt", "ai context"]},
    "SKILL_CREATION": {"weight": 4, "keywords": ["skill creation", "new skill", "init_skill", "package_skill"]},
    "AGENT_COMMAND": {"weight": 4, "keywords": ["create agent", "create command", "agent template", "command template"]},
    "FLOWCHART": {"weight": 3, "keywords": ["flowchart", "ascii diagram", "decision tree", "swimlane"]},
    "INSTALL_GUIDE": {"weight": 3, "keywords": ["install guide", "setup instructions", "prerequisite"]},
    "HVR": {"weight": 4, "keywords": ["human voice", "hvr", "voice rules", "banned words", "writing style"]},
    "PLAYBOOK": {"weight": 4, "keywords": ["playbook", "manual testing", "test scenarios", "manual test", "testing playbook"]},
    "FEATURE_CATALOG": {"weight": 4, "keywords": ["feature catalog", "feature inventory", "catalog snippet"]},
    "README_CREATION": {"weight": 3, "keywords": ["create readme", "readme creation", "write readme", "add documentation", "folder readme"]},
    "CHANGELOG": {"weight": 4, "keywords": ["changelog", "release notes", "changelog template", "release template", "create changelog", "github release"]},
    "BENCHMARK": {"weight": 4, "keywords": ["benchmark", "benchmark creation", "benchmark report", "mcp_server benchmarks", "benchmark_report.md", "skill-local benchmark", "benchmark folder", "source.md template"]},
}

RESOURCE_MAP = {
    "DOC_QUALITY": ["references/global/validation.md", "references/global/workflows.md", "references/global/core_standards.md", "references/global/evergreen_packet_id_rule.md"],
    "OPTIMIZATION": ["references/global/optimization.md", "assets/llmstxt_templates.md"],
    "SKILL_CREATION": ["references/skill_creation.md", "assets/skill/skill_md_template.md", "assets/skill/skill_readme_template.md", "assets/skill/skill_reference_template.md"],
    "AGENT_COMMAND": ["references/agent_creation.md", "assets/agent_template.md", "assets/command/command_template.md"],
    "FLOWCHART": ["assets/flowcharts/simple_workflow.md", "assets/flowcharts/decision_tree_flow.md"],
    "INSTALL_GUIDE": ["assets/readme/install_guide_template.md", "references/install_guide_creation.md"],
    "HVR": ["references/global/hvr_rules.md"],
    "PLAYBOOK": ["references/manual_testing_playbook_creation.md", "assets/testing_playbook/manual_testing_playbook_template.md"],
    "FEATURE_CATALOG": ["references/feature_catalog_creation.md", "assets/feature_catalog/feature_catalog_template.md"],
    "README_CREATION": ["references/readme_creation.md", "assets/readme/readme_template.md"],
    "CHANGELOG": ["assets/changelog_template.md"],
    "BENCHMARK": ["references/benchmark_creation.md", "assets/benchmark/benchmark_report_template.md", "assets/benchmark/source_template.md"],
}

LOADING_LEVELS = {
    "ALWAYS": [DEFAULT_RESOURCE],
    "ON_DEMAND_KEYWORDS": ["full standards", "all templates", "deep dive", "readme", "documentation", "manual testing playbook", "feature catalog", "release notes", "corpus/readme", "corpus documentation"],
    "ON_DEMAND": ["assets/frontmatter_templates.md"],
}

UNKNOWN_FALLBACK_CHECKLIST = [
    "Confirm whether this is document quality, component creation, flowchart, install guide, playbook, or catalog work",
    "Confirm the expected output file or component type",
    "Provide one example input or target document",
    "Confirm whether full templat

…

## Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [MichelKerkmeester](https://github.com/MichelKerkmeester)
- **Source:** [MichelKerkmeester/opencode--skilled-agent-loops-with-spec-kit-memory](https://github.com/MichelKerkmeester/opencode--skilled-agent-loops-with-spec-kit-memory)
- **License:** MIT

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** no
- **Filesystem access:** yes
- **Shell / process execution:** no
- **Environment & secrets:** no
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/skill-michelkerkmeester-opencode-skilled-agent-loops-with-spec-kit-memory-sk-doc
- Seller: https://agentstack.voostack.com/s/michelkerkmeester
- Browse the marketplace: https://agentstack.voostack.com/browse

---
Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.