whiteducksoftware / whiteducksoftware/flock
[1.0] Add explicit instruction Skills to AgentBuilder
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- Dominant language
- Python
- Stars
- 120
- Forks
- 14
- Avg merge
- 19h 32m
- Merged PRs (30d)
- 8
Description
Reusable native Skills are designed in feat/skills but are not implemented at the inspected branch tip. The first slice should attach ordinary SKILL.md instructions to existing typed agents.
Scope
- Implement explicit paths/globs and configured roots on AgentBuilder.with_skills(..., runtime=False, token_budget=...).
- Safely parse optional metadata; reject ambiguous names and invalid bindings before execution. Do not import code or create publishing schemas from metadata.
- Bind immutable content per agent with source/revision and an explicit budget decision; combine Skill text with the instructions the engine actually uses.
Acceptance criteria
- A deterministic signature/engine test sees a plain prose Skill in the actual prompt even with custom engine instructions.
- The agent still emits its declared artifact and triggers its normal downstream subscription.
- Malformed metadata, name collisions, unsupported engines and budget overflow fail clearly before execution; shared content does not create shared mutable bindings.
Boundaries
Context providers continue to shape artifact context. Lazy reference tools are the next slice; Skill scripts, demo injection and optimization are deferred.
References
- Implementation dependencies: #442.
- src/flock/core/agent.py
- src/flock/engines/dspy_engine.py
- docs/plans/2026-04-17-001-feat-agent-skills-internal-flock-plan.md
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start with AgentBuilder and the entry points in src/flock/core/agent.py, then inspect src/flock/engines/dspy_engine.py and the referenced implementation plan. Use the deterministic signature/engine test described in the acceptance criteria to verify prompt content, artifact emission, subscriptions, validation failures, and isolated bindings.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- ai
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Active
- Clarity
- Mostly clear
- Newbie friendliness
- 48/100