Skip to main content
Glama

recalc_signs

Recalculate automatic file signatures using content embeddings to identify duplicates and similarities without modifying YAML metadata.

Instructions

Recalculate sign_auto for all files based on content embeddings. Does not modify YAML.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dry_runNoShow changes only, do not write (default false)
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It successfully communicates the non-destructive nature regarding YAML ('Does not modify YAML'), but omits other critical behavioral traits such as performance implications of processing 'all files', side effects (does it write to a database or return values?), and what sign_auto actually represents.

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?

The description consists of exactly two high-value sentences with zero waste: the first establishes the operation and scope, while the second provides critical safety information. It is appropriately front-loaded and succinct.

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

Completeness3/5

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

For a single-parameter tool with full schema coverage, the description adequately covers the basic operation. However, given the lack of annotations, absence of an output schema, and the potentially expensive nature of recalculating embeddings for all files, the description could benefit from additional context regarding return values or execution warnings.

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

Parameters3/5

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

The input schema has 100% description coverage for the dry_run parameter, establishing a baseline score of 3. The description text does not explicitly discuss the parameter or add usage context beyond what the schema already provides.

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

Purpose4/5

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

The description clearly states the specific action (recalculate), target resource (sign_auto), scope (all files), and method (content embeddings). It implicitly distinguishes from sibling 'recalc_core_mix' by specifying 'sign_auto' rather than 'core_mix'.

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

Usage Guidelines2/5

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

While the description notes a safety constraint ('Does not modify YAML'), it provides no explicit guidance on when to use this tool versus alternatives like 'suggest_metadata' or 'recalc_core_mix', nor does it mention prerequisites such as requiring embeddings to exist first.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/KVANTRA-dev/NOUZ-MCP'

If you have feedback or need assistance with the MCP directory API, please join our Discord server