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itr-agent

itr-agent

by panchasarapavan
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Python
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ingest_ais

Capture mapped Annual Information Statement (AIS) data in the AISData schema by assessment year to enable tax pre-fill; call show_ais afterward to display the stored summary.

Instructions

Store an AIS that you have read and mapped into the AISData schema.

Submit every section, even when empty. Amounts are plain numbers in INR. Use the statement's own values. Do not compute anything. Afterwards, call show_ais to display it.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "ais": "<ais>"
    },
    "name": "ingest_ais"
  }
}

Input Schema

NameRequiredDescriptionDefault
aisYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior3/5

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

No annotations are supplied, so the description carries the full behavioral burden. It discloses two real traits — a full-payload expectation ("submit every section, even when empty") and a fidelity constraint ("do not compute anything"), the latter implying the tool stores rather than derives values. It never says whether an ingest replaces or merges with previously stored AIS data, nor what happens on malformed input.

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?

Five short sentences, front-loaded with the purpose followed by constraints and the next action. Nothing is padded and each sentence carries an instruction the agent would otherwise have to guess.

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

Completeness3/5

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

For a mutation tool with no annotations, no output schema, and zero param descriptions, the definition covers payload discipline and the follow-up step but not the semantics of the nested sections or overwrite behavior. It is workable for an agent that already knows the AIS format, incomplete for one that does not.

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 description coverage is 0% and the single ais parameter expands into eight nested section arrays with opaque field names like "description" and "category". The description adds genuine meaning for amounts (plain numbers, INR, use the statement's own values) but supplies no mapping from statement sections to schema sections, which is the real ambiguity here.

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?

"Store an AIS that you have read and mapped into the AISData schema" states a specific verb and resource, and the AIS resource distinguishes it from the other ingest_* siblings (26as, form16, trades). It stops short of naming those siblings explicitly, but an agent can still pick the right one from the name plus description.

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 concrete invocation rules — submit every section even when empty, use the statement's own values, do not compute, then call show_ais. The follow-up call to show_ais is an explicit sequencing instruction, though there is no statement about when this should be skipped or what to do if the AIS was already ingested.

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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