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SACS.ai MCP — California School District Financial Data

sacs_query_attendance

Read-onlyIdempotent

Return recovered Form A ADA observations for one official district filing.

Input Schema

NameRequiredDescriptionDefault
limitNo
offsetNo
client_idNo
dataset_refYes
district_identifierYes

Output Schema

NameRequiredDescriptionDefault
okYes
dataNo
errorNo
request_idYes
limitationsNo
data_versionYes
contract_versionNosacs.mcp.v1
source_provenanceNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.4/5.0
Behavior2/5

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

Annotations already declare read-only, idempotent, closed-world and non-destructive behavior, so the safety profile is covered. The description adds little beyond the scope hint, and it never explains what 'recovered' means (backfilled? re-derived?), how large results can be, or the meaning of the limit/offset window.

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?

A single front-loaded sentence with no filler or repetition. It is short and easy to scan, though the compactness comes partly at the cost of information covered under other dimensions.

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?

An output schema exists, so return shape need not be described. However, for a tool with five undocumented parameters, no annotations gap-filling needed but no parameter or constraint detail either, the description leaves an agent unable to construct a correct call without reading the raw schema.

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

Parameters2/5

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

Schema description coverage is 0% across five parameters, so the description must carry the burden and it does not. It never explains the 'official:<id>' dataset_ref pattern, the district_identifier format, the client_id requirement, or pagination defaults and caps.

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 names a resource ('recovered Form A ADA observations') and a scope ('one official district filing'), so the general intent is inferable. But 'recovered' and 'Form A ADA' are unexplained domain jargon, and nothing distinguishes it from siblings like sacs_query_financial_summary or sacs_district_context_pack.

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 indication of when to use this tool versus the eleven sibling query tools, no prerequisites, and no note on when a dataset_ref is appropriate. The agent must infer usage entirely from the tool name.

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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