Content
77%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.
The body is a lean, highly actionable orchestrator playbook: a deterministic router with exit-code semantics, a gated delivery loop with explicit validation and escalation caps, and hard governance rules. Its main weaknesses are the incomplete loop_controller command and the fact that every referenced file (references/ and scripts/) is absent from the bundle, leaving the disclosure structure unresolvable.
Suggestions
Ship the referenced bundle files — references/flow_forecasting_canon.md, references/agentic_delivery_governance.md, references/pm_loop_playbook.md, and the scripts (pm_goal_router.py, jira_snapshot_bridge.py, delivery_loop_gate.py) — or remove the links; as delivered, the References section and the core routing/verification workflow point at files that do not exist.
Complete the loop_controller.py example: replace 'init|next|record|verify|close ...' with at least the argument shapes for the two most common invocations (init and record), matching the copy-paste readiness of the router and gate commands.
Fold the symptom table into a single line of pointer text (or move it to the router's --help output), since the routing logic section already mandates using the script rather than the table — this trims redundant tokens and removes a source of drift between table and router.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is dense and operational — tables for symptoms and output artifacts, one-line canon citations ('refuses on < 10 completed items — thin history forecasts are lies'), and no explanations of concepts Claude already knows. Not 5: minor trimming is possible — the symptom table overlaps the deterministic router ('do not eyeball the table when a script can decide'), and a few rationale asides ('same locked-evaluator invariant as autoresearch-agent', 'that diff finds watermelon projects') are denser than needed to act. | 4 / 5 |
Actionability | Most guidance is copy-paste ready with exit-code semantics: 'python3 scripts/pm_goal_router.py --text "<the goal>" --output json' with 'Exit 0 → route_to… Exit 2 → ask ONE clarifying question… Exit 3 → no signal', and both delivery_loop_gate.py invocations with 'exit 2 = blocked' / 'exit 4 = close refused'. Not 5: 'loop_controller.py init|next|record|verify|close ...' trails with an ellipsis and no argument list, so that step is not executable as written. | 4 / 5 |
Workflow Clarity | The delivery loop is explicitly sequenced (Observe → Choose → Act → Verify → Record → Repeat-or-stop) with machine-run validation gates at plan and close, sub-skill gates layered on top ('scrum-master's ≥ 3-sprints rule, atlassian-admin's VERIFY steps'), explicit feedback control ('Max 3 attempts per task, 12 loop iterations per goal — then escalate'), and 'Never adjudicate your own verification'. This matches the anchor for explicit validation steps with feedback loops and error-recovery escalation. | 5 / 5 |
Progressive Disclosure | The body itself is well-sectioned and defers canon material to three clearly signaled references (flow_forecasting_canon.md, agentic_delivery_governance.md, pm_loop_playbook.md), but none of those reference files — nor any of the scripts the workflow depends on (pm_goal_router.py, jira_snapshot_bridge.py, delivery_loop_gate.py) — exist in the bundle, so the navigation structure cannot be verified and the links are dangling. It also leans on repo-external paths ('../scrum-master/scripts/velocity_analyzer.py', 'engineering/agent-harness/…', 'project-management/references/atlassian-mcp-tools.md') that fall outside the skill's own directory. Not 4: missing referenced files is more than a minor organization gap, since the References section and the core workflow depend on them. | 3 / 5 |
Total | 16 / 20 Passed |