whiteducksoftware / whiteducksoftware/flock

[1.0] Add explicit instruction Skills to AgentBuilder

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enhancement
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

Contributor guide

Open the contributing guide

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. 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

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