Generates a full dedicated Docusaurus page for every one of the 132 skills
(73 bundled + 59 optional) under website/docs/user-guide/skills/{bundled,optional}/<category>/.
Each page carries the skill's description, metadata (version, author, license,
dependencies, platform gating, tags, related skills cross-linked to their own
pages), and the complete SKILL.md body that Hermes loads at runtime.
Previously the two catalog pages just listed skills with a one-line blurb and
no way to see what the skill actually did — users had to go read the source
repo. Now every skill has a browsable, searchable, cross-linked reference in
the docs.
- website/scripts/generate-skill-docs.py — generator that reads skills/ and
optional-skills/, writes per-skill pages, regenerates both catalog indexes,
and rewrites the Skills section of sidebars.ts. Handles MDX escaping
(outside fenced code blocks: curly braces, unsafe HTML-ish tags) and
rewrites relative references/*.md links to point at the GitHub source.
- website/docs/reference/skills-catalog.md — regenerated; each row links to
the new dedicated page.
- website/docs/reference/optional-skills-catalog.md — same.
- website/sidebars.ts — Skills section now has Bundled / Optional subtrees
with one nested category per skill folder.
- .github/workflows/{docs-site-checks,deploy-site}.yml — run the generator
before docusaurus build so CI stays in sync with the source SKILL.md files.
Build verified locally with `npx docusaurus build`. Only remaining warnings
are pre-existing broken link/anchor issues in unrelated pages.
11 KiB
| title | sidebar_label | description |
|---|---|---|
| Subagent Driven Development — Use when executing implementation plans with independent tasks | Subagent Driven Development | Use when executing implementation plans with independent tasks |
{/* This page is auto-generated from the skill's SKILL.md by website/scripts/generate-skill-docs.py. Edit the source SKILL.md, not this page. */}
Subagent Driven Development
Use when executing implementation plans with independent tasks. Dispatches fresh delegate_task per task with two-stage review (spec compliance then code quality).
Skill metadata
| Source | Bundled (installed by default) |
| Path | skills/software-development/subagent-driven-development |
| Version | 1.1.0 |
| Author | Hermes Agent (adapted from obra/superpowers) |
| License | MIT |
| Tags | delegation, subagent, implementation, workflow, parallel |
| Related skills | writing-plans, requesting-code-review, test-driven-development |
Reference: full SKILL.md
:::info The following is the complete skill definition that Hermes loads when this skill is triggered. This is what the agent sees as instructions when the skill is active. :::
Subagent-Driven Development
Overview
Execute implementation plans by dispatching fresh subagents per task with systematic two-stage review.
Core principle: Fresh subagent per task + two-stage review (spec then quality) = high quality, fast iteration.
When to Use
Use this skill when:
- You have an implementation plan (from writing-plans skill or user requirements)
- Tasks are mostly independent
- Quality and spec compliance are important
- You want automated review between tasks
vs. manual execution:
- Fresh context per task (no confusion from accumulated state)
- Automated review process catches issues early
- Consistent quality checks across all tasks
- Subagents can ask questions before starting work
The Process
1. Read and Parse Plan
Read the plan file. Extract ALL tasks with their full text and context upfront. Create a todo list:
# Read the plan
read_file("docs/plans/feature-plan.md")
# Create todo list with all tasks
todo([
{"id": "task-1", "content": "Create User model with email field", "status": "pending"},
{"id": "task-2", "content": "Add password hashing utility", "status": "pending"},
{"id": "task-3", "content": "Create login endpoint", "status": "pending"},
])
Key: Read the plan ONCE. Extract everything. Don't make subagents read the plan file — provide the full task text directly in context.
2. Per-Task Workflow
For EACH task in the plan:
Step 1: Dispatch Implementer Subagent
Use delegate_task with complete context:
delegate_task(
goal="Implement Task 1: Create User model with email and password_hash fields",
context="""
TASK FROM PLAN:
- Create: src/models/user.py
- Add User class with email (str) and password_hash (str) fields
- Use bcrypt for password hashing
- Include __repr__ for debugging
FOLLOW TDD:
1. Write failing test in tests/models/test_user.py
2. Run: pytest tests/models/test_user.py -v (verify FAIL)
3. Write minimal implementation
4. Run: pytest tests/models/test_user.py -v (verify PASS)
5. Run: pytest tests/ -q (verify no regressions)
6. Commit: git add -A && git commit -m "feat: add User model with password hashing"
PROJECT CONTEXT:
- Python 3.11, Flask app in src/app.py
- Existing models in src/models/
- Tests use pytest, run from project root
- bcrypt already in requirements.txt
""",
toolsets=['terminal', 'file']
)
Step 2: Dispatch Spec Compliance Reviewer
After the implementer completes, verify against the original spec:
delegate_task(
goal="Review if implementation matches the spec from the plan",
context="""
ORIGINAL TASK SPEC:
- Create src/models/user.py with User class
- Fields: email (str), password_hash (str)
- Use bcrypt for password hashing
- Include __repr__
CHECK:
- [ ] All requirements from spec implemented?
- [ ] File paths match spec?
- [ ] Function signatures match spec?
- [ ] Behavior matches expected?
- [ ] Nothing extra added (no scope creep)?
OUTPUT: PASS or list of specific spec gaps to fix.
""",
toolsets=['file']
)
If spec issues found: Fix gaps, then re-run spec review. Continue only when spec-compliant.
Step 3: Dispatch Code Quality Reviewer
After spec compliance passes:
delegate_task(
goal="Review code quality for Task 1 implementation",
context="""
FILES TO REVIEW:
- src/models/user.py
- tests/models/test_user.py
CHECK:
- [ ] Follows project conventions and style?
- [ ] Proper error handling?
- [ ] Clear variable/function names?
- [ ] Adequate test coverage?
- [ ] No obvious bugs or missed edge cases?
- [ ] No security issues?
OUTPUT FORMAT:
- Critical Issues: [must fix before proceeding]
- Important Issues: [should fix]
- Minor Issues: [optional]
- Verdict: APPROVED or REQUEST_CHANGES
""",
toolsets=['file']
)
If quality issues found: Fix issues, re-review. Continue only when approved.
Step 4: Mark Complete
todo([{"id": "task-1", "content": "Create User model with email field", "status": "completed"}], merge=True)
3. Final Review
After ALL tasks are complete, dispatch a final integration reviewer:
delegate_task(
goal="Review the entire implementation for consistency and integration issues",
context="""
All tasks from the plan are complete. Review the full implementation:
- Do all components work together?
- Any inconsistencies between tasks?
- All tests passing?
- Ready for merge?
""",
toolsets=['terminal', 'file']
)
4. Verify and Commit
# Run full test suite
pytest tests/ -q
# Review all changes
git diff --stat
# Final commit if needed
git add -A && git commit -m "feat: complete [feature name] implementation"
Task Granularity
Each task = 2-5 minutes of focused work.
Too big:
- "Implement user authentication system"
Right size:
- "Create User model with email and password fields"
- "Add password hashing function"
- "Create login endpoint"
- "Add JWT token generation"
- "Create registration endpoint"
Red Flags — Never Do These
- Start implementation without a plan
- Skip reviews (spec compliance OR code quality)
- Proceed with unfixed critical/important issues
- Dispatch multiple implementation subagents for tasks that touch the same files
- Make subagent read the plan file (provide full text in context instead)
- Skip scene-setting context (subagent needs to understand where the task fits)
- Ignore subagent questions (answer before letting them proceed)
- Accept "close enough" on spec compliance
- Skip review loops (reviewer found issues → implementer fixes → review again)
- Let implementer self-review replace actual review (both are needed)
- Start code quality review before spec compliance is PASS (wrong order)
- Move to next task while either review has open issues
Handling Issues
If Subagent Asks Questions
- Answer clearly and completely
- Provide additional context if needed
- Don't rush them into implementation
If Reviewer Finds Issues
- Implementer subagent (or a new one) fixes them
- Reviewer reviews again
- Repeat until approved
- Don't skip the re-review
If Subagent Fails a Task
- Dispatch a new fix subagent with specific instructions about what went wrong
- Don't try to fix manually in the controller session (context pollution)
Efficiency Notes
Why fresh subagent per task:
- Prevents context pollution from accumulated state
- Each subagent gets clean, focused context
- No confusion from prior tasks' code or reasoning
Why two-stage review:
- Spec review catches under/over-building early
- Quality review ensures the implementation is well-built
- Catches issues before they compound across tasks
Cost trade-off:
- More subagent invocations (implementer + 2 reviewers per task)
- But catches issues early (cheaper than debugging compounded problems later)
Integration with Other Skills
With writing-plans
This skill EXECUTES plans created by the writing-plans skill:
- User requirements → writing-plans → implementation plan
- Implementation plan → subagent-driven-development → working code
With test-driven-development
Implementer subagents should follow TDD:
- Write failing test first
- Implement minimal code
- Verify test passes
- Commit
Include TDD instructions in every implementer context.
With requesting-code-review
The two-stage review process IS the code review. For final integration review, use the requesting-code-review skill's review dimensions.
With systematic-debugging
If a subagent encounters bugs during implementation:
- Follow systematic-debugging process
- Find root cause before fixing
- Write regression test
- Resume implementation
Example Workflow
[Read plan: docs/plans/auth-feature.md]
[Create todo list with 5 tasks]
--- Task 1: Create User model ---
[Dispatch implementer subagent]
Implementer: "Should email be unique?"
You: "Yes, email must be unique"
Implementer: Implemented, 3/3 tests passing, committed.
[Dispatch spec reviewer]
Spec reviewer: ✅ PASS — all requirements met
[Dispatch quality reviewer]
Quality reviewer: ✅ APPROVED — clean code, good tests
[Mark Task 1 complete]
--- Task 2: Password hashing ---
[Dispatch implementer subagent]
Implementer: No questions, implemented, 5/5 tests passing.
[Dispatch spec reviewer]
Spec reviewer: ❌ Missing: password strength validation (spec says "min 8 chars")
[Implementer fixes]
Implementer: Added validation, 7/7 tests passing.
[Dispatch spec reviewer again]
Spec reviewer: ✅ PASS
[Dispatch quality reviewer]
Quality reviewer: Important: Magic number 8, extract to constant
Implementer: Extracted MIN_PASSWORD_LENGTH constant
Quality reviewer: ✅ APPROVED
[Mark Task 2 complete]
... (continue for all tasks)
[After all tasks: dispatch final integration reviewer]
[Run full test suite: all passing]
[Done!]
Remember
Fresh subagent per task
Two-stage review every time
Spec compliance FIRST
Code quality SECOND
Never skip reviews
Catch issues early
Quality is not an accident. It's the result of systematic process.