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Forget

forget
DestructiveIdempotent

Delete a previously stored memory by key. Use when context is stale, the task is done, or you want to clear sensitive data the agent saved earlier. Pair with remember and recall.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keyYesMemory key to delete

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already indicate destructiveHint=true and idempotentHint=true. The description adds context about clearing sensitive data and deleting previously stored memories, reinforcing the destructive nature without contradicting annotations.

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?

Two sentences clearly state purpose and usage guidance with no wasted words. The description is front-loaded with the primary action.

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 single-parameter destructive tool with clear annotations and no output schema, the description provides sufficient context for selection and invocation. It explains when to use and how it relates to siblings.

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?

Schema coverage is 100% with the parameter described as 'Memory key to delete.' The description mentions 'by key' but does not add further semantic detail beyond the schema, so baseline 3 is appropriate.

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 uses a specific verb and resource: 'Delete a previously stored memory by key.' It clearly distinguishes from sibling tools like remember and recall, stating the action and object.

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?

It provides explicit when-to-use conditions: 'Use when context is stale, the task is done, or you want to clear sensitive data the agent saved earlier.' It also points to related tools: 'Pair with remember and recall.'

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

A3.8/5.0
Disambiguation2/5

ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded share the same routing and response shape, while the polymarket_* family and company-research tools (entity_profile, compare_entities, recent_changes) have overlapping triggers. The descriptions are detailed, but an agent can still easily select the wrong variant.

Naming Consistency3/5

Names are readable and consistently snake_case, with recognizable families like ask_pipeworx_*, polymarket_*, and pipeworx_*. However, conventions mix verb_noun patterns (compare_entities, resolve_entity) with noun phrases (entity_profile, recent_alerts, pipeworx_trending), so the pattern is not fully consistent.

Tool Count2/5

32 tools is heavy for any single server, and nearly all of them are unrelated to the 'Jsonschema' name—only validate_json_schema actually addresses JSON Schema. Even viewed as a Pipeworx data/research toolkit, the set feels bloated with near-duplicate query and prediction-market variants.

Completeness2/5

If the intended domain is JSON Schema, the surface is severely incomplete: only validation exists, with no parsing, generation, or schema-management tools. If the intended domain is the Pipeworx data-research suite, it is more complete but still lacks a raw record-fetch tool despite citations promising pipeworx:// URIs, and the server-name mismatch creates a confusing dead end.