Content
76%Weight 40%Scale 1-5Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
A tight, well-sectioned reference-style skill with excellent token efficiency and mostly concrete guidance anchored by a real-syntax code pattern. The main gaps are the absence of a sequenced workflow with validation checkpoints for the evolve/refine lifecycle, a core example that is not fully runnable, and file citations that do not resolve within the skill bundle.
Suggestions
Add a short numbered workflow for the playbook lifecycle with an explicit validation checkpoint (e.g., 1. Grow with playbook() 2. Attach and run 3. Evolve with verification and exact rollback 4. Validate the learned rules with no-key examples before rendering), turning the implicit When-To-Use sequence into explicit steps with feedback loops.
Make the Core Pattern runnable or explicitly justify the placeholders — define how `llm`, `examples`, and `metric_fn` are constructed (e.g., one line each or a pointer to the exact example file in the package's examples/ directory).
Clarify where `API.md`, `axir-capabilities.json`, and `examples/` live (generated package vs. skill bundle) so a reader knows where to navigate, and link the specific example files for each When-To-Use bullet.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is lean and fully sectioned — every line carries package-specific information Claude would not know ("Real network support: yes", "Scripted no-key transport support: yes", "Runtime profiles: `javascript-quickjs`, `python-pyodide`") with zero padding or explanation of known concepts. It clearly matches anchor 5 (lean, assumes Claude's competence, every token earns its place) rather than anchor 4, which reserves room for trimmable over-explanation. | 5 / 5 |
Actionability | The Core Pattern shows real import and call syntax ("from axllm import ax, playbook", "pb = playbook(program, {\"studentAI\": llm})", "pb.evolve(examples, metric_fn)"), and the Guardrails give concrete directives ("Start from package examples for exact native syntax", "Use `no-key` examples for deterministic local checks"). It is not anchor 5 because the snippet is not copy-paste runnable — `llm`, `examples`, and `metric_fn` are undefined placeholders with no metric signature — and "Relevant API Surface" lists optimizer names without any call shape; but it is well above anchor 3's pseudocode level. | 4 / 5 |
Workflow Clarity | The "When To Use" bullets imply a lifecycle (grow a playbook → attach to an agent → evolve from run-end failures → refine online/offline → render and inject) but there is no sequenced workflow and no validation checkpoints — the only check-adjacent guidance is in Guardrails ("Start from package examples", "no-key examples for deterministic local checks"). This fits anchor 3 (sequence implicit, checkpoints missing); anchor 4 would require an explicit ordered sequence with most checkpoints present. | 3 / 5 |
Progressive Disclosure | The body is short (~44 lines) and cleanly sectioned (When To Use, Package Facts, Core Pattern, Relevant API Surface, Guardrails), which on its own merits a 5 under the simple-skill exception. It drops to anchor 4 because the "Package Facts" section cites `API.md`, `axir-api.json`, `axir-capabilities.json`, and `examples/` as lookup targets, yet no such files exist in the skill bundle (no references/, scripts/, or assets/ directories) — navigation to them is ambiguous since it is never clarified whether they live in the generated package or alongside the skill. | 4 / 5 |
Total | 16 / 20 Passed |