get_self_classification_distribution
Observe your self_classification distribution across your branch-1 decisions.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| auth_token | Yes | Your DA agent auth token |
Decision Anchor
Schema Changelog
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
- Added
TDQS
C2.9/5.0
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. 'Observe' implies read-only, but no information is given about side effects, authorization needs beyond the generic auth_token, or performance characteristics.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no superfluous words. It is appropriately sized for a simple tool, though slight expansion could improve clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no output schema, but the description does not explain the return format (e.g., what the distribution looks like, keys, values). For a simple tool, agents need to know what to expect from the response.
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% (only auth_token, which is described). The description does not add additional meaning to the parameter beyond what the schema provides, so baseline score applies.
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 verb 'Observe' and the resource 'self_classification distribution' with scope 'across your branch-1 decisions.' It distinguishes from siblings like get_decision_metadata_distribution and list_classifications by focusing on self_classification specifically, though 'self_classification' is not defined.
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?
The description provides no guidance on when to use this tool versus alternatives (e.g., get_decision_metadata_distribution) or any prerequisites or conditions for use.
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
A3.5/5.0
Disambiguation4/5
Most tools have clear, distinct purposes, but a few overlap in function: get_decision_metadata_distribution and get_self_classification_distribution are both distribution getters, and observe_environment and observe_pattern could be confused. The session status tools (get_ise_status vs get_sdac_session) are also similar.
Naming Consistency5/5
All tool names follow a consistent snake_case verb_noun pattern (create_, get_, list_, observe_, run_, end_, exit_, confirm_, etc.). There are no stylistic deviations or mixed conventions.
Tool Count2/5
With 30 tools, the surface is heavy. Several tools could be consolidated (e.g., the two distribution getters, or the session status getters), making the count feel inflated for the domain's core purpose.
Completeness3/5
The core decision lifecycle (create, confirm, get, list) is covered well, and sessions/observation/marketplace add breadth. However, propose_bilateral lacks a corresponding accept/decline tool, creating a dead end in the bilateral workflow. Also, no way to fetch detailed info on a specific marketplace tool.