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model-selection

Per-agent model selection with 4-layer hierarchy and fallback chains

63

Quality

75%

Does it follow best practices?

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SecuritybySnyk

Passed

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tessl review fix ./.copilot/skills/model-selection/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

100%

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

The SKILL.md body is a lean, well-organized, highly actionable reference with clear multi-step workflows, explicit validation before destructive config writes, and no pedagogical filler or nested reference chains. It earns full marks across conciseness, actionability, workflow clarity, and progressive disclosure, with only minor optional tightening of the redundant "Key principle" paragraph.

DimensionReasoningScore

Conciseness

The body is lean and assumes Claude's competence — no pedagogy about what an LLM or model tier is, organized as tables and numbered steps. It is leaner than the score-2 anchor example (which editorializes "It's a good library that handles most formats well"); a slight redundancy where the "Key principle" paragraph restates the Layer 0 table row keeps it just inside 3 rather than flagging it at 2.

3 / 3

Actionability

Provides fully concrete, copy-paste-ready guidance: exact config field names (defaultModel, agentModelOverrides.{name}), a full JSON schema, exact trigger phrases, and exact acknowledgment templates. This is instruction-only (no executable code) which the rubric permits when guidance is actionable; not 2 because no key details are vague or missing.

3 / 3

Workflow Clarity

Multi-step processes are clearly sequenced (On Session Start, On Every Agent Spawn, When User Sets, When User Clears) with an explicit VALIDATE checkpoint ("VALIDATE the model ID against the catalog") before the destructive config write, plus a STOP checklist. Matches score 3 ("Clear sequence with explicit validation steps… checklists"); not 2 because validation and checkpoints are explicit, not 1 because the sequence is unambiguous.

3 / 3

Progressive Disclosure

No references/, scripts/, or assets/ bundle directories exist and the body has no markdown links to external files, so there is no nested reference chain to penalize. The single self-contained document is cleanly sectioned (SCOPE, Context, Hierarchy, AGENT WORKFLOW, Config Schema, Fallback Chains); per the simple-skills scoring note, well-organized sections without need for external refs score 3. Not 2 because organization is strong and nothing is poorly signaled.

3 / 3

Total

12

/

12

Passed

Description

50%

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 states a clear single-purpose action but omits any "Use when…" trigger guidance and lacks natural user-facing trigger terms, instead using internal jargon like "agent spawn." This limits activation quality and caps both completeness and trigger-term scores. Adding an explicit trigger clause with common user phrasings would raise most dimensions.

Suggestions

Add an explicit "Use when…" clause naming the situations that should activate this skill (e.g. "Use when deciding which model to assign to an agent, when the user asks to switch or pin a model, or when picking a model for a new spawn").

Replace internal jargon ("agent spawn") with natural user-facing terms a person would actually say, such as "pick a model", "switch to opus", or "use a different model for this task".

Expand the action list beyond the single verb "Determines" to concrete capabilities (e.g. "Resolves a model per spawn, persists per-agent and default model preferences, and falls back within tier on failure") to push specificity toward 3.

DimensionReasoningScore

Specificity

Quotes "Determines which LLM model to use for each agent spawn" — names a concrete action over a defined domain, but it is a single action rather than multiple specific ones. Matches the score-2 anchor "Names domain and some actions, but not comprehensive"; not 3 because no list of actions, not 1 because a real action is named.

2 / 3

Completeness

States what the skill does ("Determines which LLM model to use for each agent spawn") but has no "Use when…" clause or equivalent explicit trigger. Per the judging guideline, a missing "Use when…" clause caps completeness at 2; not 1 because the what is clearly present, not 3 because the when is absent.

2 / 3

Trigger Term Quality

No natural user-facing trigger phrasings (e.g. "pick a model", "switch to opus", "use a different model"); "agent spawn" is internal jargon users would not say. Matches score 2 ("Some relevant keywords but missing common variations") because "model" is relevant; not 3 due to lack of natural variations, not 1 because relevant keywords are present.

2 / 3

Distinctiveness Conflict Risk

The model-selection niche is reasonably distinct (orchestration concern) but the description offers no distinct trigger phrasing to lock it away from adjacent skills. Matches score 2 ("Somewhat specific but could still overlap"); not 3 because no distinct triggers, not 1 because it is not generic.

2 / 3

Total

8

/

12

Passed

Validation

93%

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

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

15

/

16

Passed

Repository
bradygaster/squad
Reviewed

Table of Contents

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