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haggl.ai

haggl_get_my_offers

Read-onlyIdempotent

Read what haggl.ai holds for the user's haggl ID: when it was created and the negotiations, offers and codes linked to it, newest first.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
haggl_idYesThe user's haggl ID.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
codeNoPresent only when the call failed: a machine-readable error code, e.g. quote_uncertain or rate_limited.
errorNoPresent only when the call failed: what went wrong.
offersNoNegotiations linked to this haggl ID, newest first.
recordNoWhat the record holds: verified purchases by category and offer counts.
consentNoThe consent on record: version, time and channel.
recoveryNoWhen the outcome is uncertain: the tool and session_id to read before retrying.
retryableNoWhether the same call may be retried.
created_atNoISO 8601 time the haggl ID was created.
last_used_atNoISO 8601 time it was last used.
retry_after_secondsNoWhen rate limited: seconds to wait before retrying.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, covering the safety profile. The description adds the ordering behavior ('newest first') and the breadth of linked objects, which is genuinely useful, but with an output schema present it leaves return details to be discovered there.

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?

One sentence, tightly front-loaded on the verb and scope, with the returned contents and sort order packed in without filler. Every clause carries information.

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 a rich annotation set, a fully documented single parameter, and an output schema to describe returns, the description supplies enough to call the tool correctly. The only real gap is the absence of explicit sibling routing, which is minor at this complexity.

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% with a single required haggl_id already documented as 'The user's haggl ID.' The description only repeats that framing and adds no format, sourcing, or validation detail beyond the schema. Baseline 3 applies.

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?

States a specific verb (Read) and resource (what haggl.ai holds for the user's haggl ID), and enumerates the payload: creation time, negotiations, offers, codes. It is distinguishable from haggl_get_negotiation and haggl_get_bids by being the aggregate for the whole ID, though it never names those siblings explicitly.

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

Usage Guidelines3/5

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

The phrase 'for the user's haggl ID' implies a broad, account-level read, but there is no explicit when-to-use guidance or routing against nearby siblings like haggl_get_negotiation (single negotiation) or haggl_get_bids (bids only). Usage must be inferred from the scope wording.

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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