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jgravelle
by jgravelle

check_embedding_drift

Detect when your embedding provider has drifted from the pinned baseline by comparing a canary string's cosine similarity, preventing silent degradation of semantic search.

Instructions

Detect whether the embedding provider has drifted since it was pinned. Column embeddings power semantic search_data and find_similar_columns; if the provider model changes underneath a stored index, saved vectors stop matching the live encoder and semantic ranking quietly degrades. Pins a 16-string canary in /embed_canary.json and recomputes it on demand, reporting cosine drift. Call with force=true once to set the baseline, then again after a suspected provider change. Sibling of jcodemunch / jdocmunch check_embedding_drift.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
forceNoRe-embed and re-pin the canary baseline (set once to establish it).
thresholdNoCosine-distance alarm threshold; alarm is true when the worst canary drifts past it.
Behavior4/5

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

The description discloses that the tool pins a 16-string canary file, recomputes it on demand, and reports cosine drift. It also explains why drift matters (semantic ranking quietly degrades). Since annotations only state readOnlyHint=false, the description adds meaningful side-effect context beyond the annotation.

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 well-structured and front-loaded with the core purpose. It is slightly verbose but every sentence contributes context except the final sibling reference, which is somewhat obscure and could be omitted. Overall, it remains compact for the complexity involved.

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

Completeness4/5

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

Given no output schema and moderate complexity, the description provides sufficient context: why the tool exists, what it does, and how to use it. It could mention the exact return format (e.g., drift value and alarm boolean), but the schema and parameter descriptions fill most gaps. The description is adequate for an agent to invoke the tool correctly.

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?

Schema coverage is 100% with both parameters described. The description adds context for 'force' (establish baseline) and ties 'threshold' to the alarm condition, reinforcing the schema descriptions and clarifying the intended usage flow.

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's purpose: detecting embedding provider drift since a pinned baseline. It specifies the resource (embedding provider/canary file) and the mechanism (cosine drift), distinguishing it from schema drift or validation tools among siblings.

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

Usage Guidelines4/5

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

Explicit usage guidance is provided: call with force=true once to set the baseline, then again after a suspected provider change. It does not explicitly exclude alternatives or compare with other drift-related tools, but the context is clear enough for an agent to decide when this tool is appropriate.

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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