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Attendance by subject

get_subject_frequency
Read-only

Retrieve attendance counts and ratios for each subject, optionally within a date range of up to 371 days, to analyze subject-level attendance patterns.

Instructions

Get attendance counts and ratios per subject, optionally within a window of up to 371 days. For overall totals use get_attendance_frequency.

Input Schema

NameRequiredDescriptionDefault
date_toNoLast day, YYYY-MM-DD, inclusive; at most 370 days after the first.
date_fromNoFirst day, YYYY-MM-DD, inclusive.
account_aliasYesLogin alias from list_accounts.

Output Schema

NameRequiredDescriptionDefault
itemsYes
date_toYes
identityYes
date_fromYes
paginationNo
observationYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv2.5.0
    • removedOutput schema / $defs / Pagination / additionalProperties
      Removed value: -false
    • removedOutput schema / additionalProperties
      Removed value: -false
  2. Changed4 schema fields changedv2.3.1
    • addedInput schema / properties / account_alias / description
      Added value: +"Login alias from list_accounts."
    • changedInput schema / properties / account_alias / pattern
      Previous value: -"^(?:[^\\s\\x00-\\x1f\\x7f]|[^\\s\\x00-\\x1f\\x7f](?:[^\\s\\x00-\\x1f\\x7f]| )*[^\\s\\x00-\\x1f\\x7f])$"New value: +"^[^\\s\\x00-\\x1f\\x7f](?: *[^\\s\\x00-\\x1f\\x7f])*$"
    • addedInput schema / properties / date_from / description
      Added value: +"First day, YYYY-MM-DD, inclusive."
    • addedInput schema / properties / date_to / description
      Added value: +"Last day, YYYY-MM-DD, inclusive; at most 370 days after the first."
  3. First observed

TDQS

A4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so safety is covered. The description adds the aggregation nature (counts and ratios) and the ~371-day window cap, but the latter is already stated in the schema and the return shape is covered by the output schema, so the incremental behavioral disclosure is modest.

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, zero filler, with the purpose front-loaded and the sibling routing placed immediately after so the agent can redirect before reading the schema.

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?

With full schema coverage, an output schema and read-only annotations, the description covers purpose, scope and the closest alternative. The one gap is behavior when date_from/date_to are omitted (all-time vs. current term), which an agent may need in order to pick default invocation.

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% and each parameter carries its own description (inclusive dates, 370-day gap limit, alias from list_accounts). The description only restates the window size and adds no new semantics such as defaults when dates are omitted, so it sits at the baseline.

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?

States a specific verb and resource (get attendance counts and ratios per subject) plus a scoping qualifier (optional date window), and explicitly names the sibling it is not (get_attendance_frequency for overall totals). An agent can distinguish it from get_attendance, get_attendance_window and get_attendance_detail by the 'per subject' aggregation alone.

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?

Gives an explicit routing rule: 'For overall totals use get_attendance_frequency.' That is a concrete when-to-use-else cue. It stops short of addressing the other attendance siblings (get_attendance, get_attendance_detail, get_attendance_window), which is the only missing piece for a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.