perception_embed
[Sub-phase 4.2 — NOT YET IMPLEMENTED] Will generate Clay v1.5 embeddings.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| tile_id | Yes | tile_id from perception_fetch_tile result |
mcp-perception
by com.geiant
Schema Changelog
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
- First observed
TDQS
C2.8/5.0
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. It transparently states the tool is 'NOT YET IMPLEMENTED', which is an important behavioral trait (calling it will likely fail or do nothing). However, it does not describe expected errors, safety, or any side effects, and the future tense is ambiguous for current behavior.
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, concise sentence that front-loads the critical 'NOT YET IMPLEMENTED' status. It is efficient, but it lacks substantive detail that might be expected even for a placeholder, so it doesn't earn a 5.
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?
Given the tool has one parameter, no output schema, and no annotations, the description is very incomplete. It provides no context about what embeddings are for, how they relate to perception_fetch_tile, or any use-case information. The 'NOT YET IMPLEMENTED' status explains its unavailability but does not help an agent understand the tool's intended role.
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 already provides 100% coverage with a clear description for tile_id ('tile_id from perception_fetch_tile result'). The description adds no additional parameter semantics, so the baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a future intent ('Will generate Clay v1.5 embeddings') but is not currently implemented, so it does not describe actual current functionality. The verb 'generate' and resource 'embeddings' provide some specific purpose, but the explicit 'NOT YET IMPLEMENTED' makes it vague as a description of a usable tool.
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?
There is no guidance on when to use this tool or how to choose it over siblings like perception_classify or perception_fetch_tile. The 'NOT YET IMPLEMENTED' label implies it should not be used, but there is no explicit direction or alternative suggested.
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
Disambiguation5/5
Each tool has a distinct purpose within its domain: gns_* tools handle compliance reporting, trust scoring, epoch rolling, and chain verification, while perception_* tools handle tile fetching, classification, embedding, and weather queries. Even similar tools like gns_get_compliance_report and gns_get_trust_score are clearly differentiated by scope (full report vs quick score).
Naming Consistency3/5
The gns_* tools follow a consistent verb_noun pattern (get_compliance_report, get_trust_score, roll_epoch, verify_chain), but perception_* tools mix styles: perception_fetch_tile is verb_noun, perception_classify and perception_embed are just verbs, and perception_weather is a noun. The two prefixes (gns_ vs perception_) also introduce a split, though each group is internally readable.
Tool Count5/5
Eight tools is well-scoped for a server that combines two related functions: AI-powered earth observation and cryptographic compliance auditing. Each tool serves a distinct role and there are no redundant utilities, making the count feel intentional and complete.
Completeness4/5
The core workflows are covered: fetch a tile, classify it, embed it (though not yet implemented), and weather queries for context, with a full compliance trail via breadcrumbs, epochs, and verification. The only notable gap is that perception_embed is explicitly marked as not implemented, leaving a placeholder in the tool surface, but the rest of the pipeline is functional.