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multi-agent-patterns

Design multi-agent architectures for complex tasks. Use when single-agent context limits are exceeded, when tasks decompose naturally into subtasks, or when specializing agents improves quality.

Quality

62%

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tessl review fix ./antigravity/skills/multi-agent-patterns/SKILL.md

The canonical home for this skill is multi-agent-patterns in NeoLabHQ/context-engineering-kit

SKILL.md
Quality
Evals
Security

Quality

Content

35%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 reads as an architectural survey rather than an actionable skill: conceptual explanation dominates, implementation guidance stays at the outline level, and an entire second topic (memory system design) is inlined with zero reference files. The structural bones (patterns with when-to-use/advantages/disadvantages, failure modes with mitigations) are good, but the skill needs drastic trimming, executable implementation detail, and splitting into reference files.

Suggestions

Cut the 'Memory System Design' section (roughly 120 lines) entirely or move it to a separate references/ file referenced in one line; it is a distinct topic and mostly explains vector stores, knowledge graphs, and benchmark data Claude already knows.

Replace the outline-style implementation blocks with concrete, executable guidance: an actual Task-tool invocation prompt template for dispatching a subagent, a sample shared-state file format (e.g., a JSON task-list schema), and a example command definition showing supervisor-to-subagent routing.

Compress each pattern's when-to-use/advantages/disadvantages into a short table and consolidate the duplicated context-isolation prose (stated in the intro, Core Concepts, and its own section) into one place.

DimensionReasoningScore

Conciseness

The ~370-line body contains several padded sections explaining concepts Claude already knows: the entire 'Memory System Design' half describes what vector stores and knowledge graphs are, includes a vendor benchmark table (Zep, MemGPT, GraphRAG, Recursive Summarization), and restates the context-memory spectrum three times. This matches 'noticeably verbose; several unnecessary explanations or padded sections' rather than anchor 3, because the padding spans entire sections rather than isolated sentences.

2 / 5

Actionability

The 'Claude Code Implementation' blocks are numbered outlines inside code fences, not executable commands, and no concrete Task-tool prompts, command definitions, or file templates are provided. Guidance like 'let subagents write directly to shared files' and 'implement output constraints' remains a high-level hint missing the specific steps to execute, matching anchor 2; it does not reach anchor 3 because even the pseudocode blocks omit the concrete artifacts (prompts, file formats, commands) a reader would need.

2 / 5

Workflow Clarity

Sequences exist ('Command as Supervisor' gives a 4-step dispatch flow, failure-mode sections pair each failure with a mitigation), and validation guidance appears as principles ('Validate agent outputs before passing to consumers', 'Set iteration limits'). However, validation is never sequenced as an explicit checkpoint in an actual workflow, so it matches 'steps listed but validation gaps; checkpoints missing or implicit' rather than anchor 4.

3 / 5

Progressive Disclosure

Section headers organize the content reasonably well, but the entire 370-line treatise lives inline in SKILL.md with no bundle files at all; the 100+ line 'Memory System Design' section and the benchmark table clearly belong in separate reference files. This matches 'some structure but could be better organized; content that should be separate is inline'; not anchor 2 because substantial section-level structure does exist.

3 / 5

Total

10

/

20

Passed

Description

71%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.

The description is well-formed: third-person, concise, with an explicit and specific 'Use when' clause covering three trigger conditions. Its main weakness is thin action coverage in the 'what' portion and missing common natural synonyms (orchestrate, subagents, parallelize) that users would likely say.

Suggestions

Expand the 'what' clause with 2-3 more concrete capabilities, e.g., 'Design multi-agent architectures: choose orchestration patterns, define subagent roles and context boundaries, and structure file-based coordination between agents.'

Add natural trigger synonyms users would say, such as 'orchestrate agents', 'subagents', 'parallelize work', or 'fan out tasks' to the 'Use when' clause.

DimensionReasoningScore

Specificity

The description names the domain ('multi-agent architectures') and one concrete action ('Design'), matching the anchor for 1-2 concrete actions without comprehensive coverage. It does not list several specific actions (e.g., orchestrating subagents, defining handoff protocols, structuring shared state files), so it falls below anchor 4.

3 / 5

Completeness

It explicitly answers both what ('Design multi-agent architectures for complex tasks') and when, with three concrete trigger clauses ('Use when single-agent context limits are exceeded, when tasks decompose naturally into subtasks, or when specializing agents improves quality'). This mirrors the anchor-5 exemplar structure; not anchor 4 because the 'when' is already fully explicit and specific.

5 / 5

Trigger Term Quality

Relevant keywords are present ('multi-agent', 'subtasks', 'specializing agents', 'single-agent context limits'), but common natural variations users would actually say are missing: 'orchestrate', 'subagents', 'parallelize', 'swarm', 'fan out'. This matches 'some relevant keywords but missing common variations or synonyms' rather than anchor 4's 'a few natural terms missing'.

3 / 5

Distinctiveness Conflict Risk

Multi-agent architecture design is a clear niche with distinct triggers around context limits and task decomposition, but it overlaps with closely related orchestration and workflow-planning skills, giving minor overlap risk. Not anchor 5 because 'complex tasks' and 'specializing agents' could also plausibly trigger those adjacent skills.

4 / 5

Total

15

/

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

NeoLabHQ/context-engineering-kit

Path

antigravity/skills/multi-agent-patterns/SKILL.md

Reviewed

Table of Contents

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