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Glama

Load Skill

load_skill
Read-onlyIdempotent

Load the full SKILL.md body for one skill by canonical dot-notation name (e.g. "research.foundation", "research.methodologies.desk-synthesis", "shared.registers.cinema-mode"). Returns frontmatter + body + content_hash. Verifies content_hash against the registry and surfaces drift if the registry is out of sync with disk. Use AFTER list_skills to pick the right skill. For register-type skills with references/ folders, follow with load_skill_reference to pull specific references. Free, read-only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesCanonical skill name in dot-notation (e.g. "research.foundation", "research.methodologies.desk-synthesis", "shared.registers.cinema-mode"). Find via list_skills first.

TDQS

A4.9/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint, idempotentHint, and openWorldHint. The description adds valuable behavioral context: 'Verifies content_hash against the registry and surfaces drift if the registry is out of sync with disk,' disclosing a verification step not evident from annotations. No contradiction.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Four sentences, front-loaded with the primary function. Examples, sequencing advice, and return details are included without redundancy. Every sentence serves a purpose, and the structure is logical.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple input schema (one parameter, no output schema) with rich annotations, the description fully covers what the tool does, what it returns (frontmatter + body + content_hash), and how to integrate it with other tools. No gaps remain.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Only one parameter 'name' exists, and its schema description already covers format and examples. The description reinforces this with 'canonical dot-notation name (e.g. ...). Find via list_skills first,' adding practical usage guidance beyond the schema. Since schema coverage is 100%, baseline is 3, but the additional context merits a 4.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool loads the full SKILL.md body for a skill by canonical dot-notation name. It specifies the action (load), resource (SKILL.md body), and identifier format. It effectively distinguishes itself from sibling tools like list_skills (listing) and load_skill_reference (loading references).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly advises 'Use AFTER list_skills to pick the right skill' and 'For register-type skills with references/ folders, follow with load_skill_reference,' providing clear context for when and when not to use this tool. It also notes the tool is 'Free, read-only,' guiding appropriate usage.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A3.7/5.0
Disambiguation4/5

Despite the high tool count, most tools have distinct purposes with thorough descriptions that specify when to use each. Some overlap exists among creative direction tools (call_creative_worlds vs chat_with_creative_worlds), but the descriptions clarify usage patterns.

Naming Consistency3/5

Naming conventions are inconsistent overall: some follow verb_noun (create_powersource_url, decode_ad), others use noun_verb or compound names (adformula_intelligence, fleet_analytics_overview). However, subgroups like dispatch_* and list_*_presets maintain internal consistency.

Tool Count2/5

112 tools is far beyond the typical 3-15 range for well-scoped servers. While the server covers a broad domain, the sheer number likely overwhelms agents and suggests insufficient consolidation of related operations.

Completeness4/5

The tool set covers core creative intelligence workflows: brand analysis, ad decoding, script generation, creative direction, and research. Minor gaps exist (e.g., no social media publishing tools), but the main use cases are well-supported.