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parallel

Multi-agent pipeline orchestrator that plans and dispatches parallel development tasks to worktree agents. Reads project context, configures task directories with PRDs and jsonl context files, and launches isolated coding agents. Use when multiple independent features need parallel development, orchestrating worktree agents, or managing multi-agent coding pipelines.

Quality

87%

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SKILL.md
Quality
Evals
Security

Quality

Content

75%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The body is a well-structured, command-dense orchestration guide with a clear startup sequence, explicit decision criteria between the two planning options, and a validation step before launching agents. It consistently lands just below excellent: Option A's undefined $TASK_DIR, absent error-recovery loops, and some duplicated/user-facing content keep every dimension at 4.

Suggestions

In Option A, show how to capture the task directory that plan.py outputs (e.g. an assignment to TASK_DIR) so the subsequent start.py "$TASK_DIR" command is actually executable.

Add a brief error-recovery loop after validation and plan.py — e.g. what to fix and re-run when task.py validate fails, and what to do when plan.py rejects a requirement as unclear or too large.

Trim duplication and user-facing content: merge the Core Rules restatement of the role definition, and move the User Available Skills table and Monitoring Commands (which are for the user, not the AI) out of the AI-facing body or condense them.

DimensionReasoningScore

Conciseness

The body is command-first and lean — full bash invocations with no explanation of concepts Claude already knows — but contains minor trimmable redundancy: "You don't write code directly" in Role Definition is restated as "Don't write code directly" in Core Rules, and the [AI]/[USER] marker table plus user-facing tables add overhead. This matches the 4-anchor ("efficient; minor instances that could be trimmed") rather than 5, since not every section earns its place.

4 / 5

Actionability

Mostly executable, copy-paste-ready commands (task.py create/init-context/set-branch/set-scope/add-context/validate, multi_agent/plan.py and start.py with concrete flags), with one notable gap: Option A instructs `start.py "$TASK_DIR"` but never shows how TASK_DIR is assigned after plan.py runs. This fits the 4-anchor ("concrete code or commands with minor gaps"), not 5 ("fully executable… specific examples cover the common cases").

4 / 5

Workflow Clarity

The sequence is clear: a 4-step startup flow, explicit decision criteria for Option A vs B, and Option B includes a validation checkpoint ("python3 ./.trellis/scripts/task.py validate \"$TASK_DIR\"") before starting. However, there is no error-recovery feedback loop (what to do when validate fails) and no guidance for when plan.py "may reject if unclear/too large", so it matches the 4-anchor rather than 5 ("explicit validation steps; feedback loops for error recovery").

4 / 5

Progressive Disclosure

There are no bundle files (references/, scripts/, assets/ are absent) and the skill is a single well-organized file with clear section headers (Startup Flow, Planning, Monitoring, Core Rules), so navigation is easy. It sits at the 4-anchor ("good structure; most content appropriately placed; minor organization gaps") rather than 5 because user-facing content (the User Available Skills table and Monitoring Commands) is inlined in an AI-facing skill and the file is ~190 lines rather than a compact overview pointing elsewhere.

4 / 5

Total

16

/

20

Passed

Description

92%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong description: it uses third person, states several concrete actions with specific artifacts (PRDs, jsonl context files), and closes with an explicit "Use when" clause containing natural trigger phrases for a well-defined niche. The only weakness is slightly limited keyword variation in the trigger terms.

DimensionReasoningScore

Specificity

The description lists multiple concrete actions covering the full orchestration cycle — "plans and dispatches parallel development tasks to worktree agents", "Reads project context", "configures task directories with PRDs and jsonl context files", and "launches isolated coding agents" — including concrete artifacts like PRDs and jsonl context files. This matches the 5-anchor ("multiple specific concrete actions; comprehensive coverage") rather than 4, since no meaningful AI-executed action in the workflow is omitted.

5 / 5

Completeness

It clearly answers both questions: the "what" (orchestrate, read context, configure task directories, launch agents) and an explicit "when" ("Use when multiple independent features need parallel development, orchestrating worktree agents, or managing multi-agent coding pipelines"). This matches the 5-anchor pattern of both what and when with concrete trigger phrases, not the 4-anchor where the when is only adequate.

5 / 5

Trigger Term Quality

The "Use when" clause includes good natural keywords — "multiple independent features need parallel development", "orchestrating worktree agents", "managing multi-agent coding pipelines" — that users would plausibly say. It falls short of the 5-anchor because common variations and synonyms like "parallelize", "run tasks concurrently", or "multiple features at once" are missing.

4 / 5

Distinctiveness Conflict Risk

Phrases like "Multi-agent pipeline orchestrator", "worktree agents", and "multi-agent coding pipelines" establish a clear niche with distinct triggers that few other skills would share. It fits the 5-anchor ("clear niche with distinct triggers; minimal conflict risk") rather than 4, since overlap risk with closely related skills is minimal.

5 / 5

Total

19

/

20

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository

202780181/lingxiData

Path

.codex/skills/parallel/SKILL.md

Reviewed

Table of Contents

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