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Glama

price_zero_coupon_bond

Price a zero-coupon bond using user-supplied market data, a discounting curve, and a preset; optionally include duration and convexity details.

Instructions

Price a zero-coupon bond (POST /price-zero-coupon-bond).

Args: market_data_source: where the market numbers in this call come from. user_pasted (the user pasted or typed the numbers in this conversation), user_file (the user attached a file/screenshot the numbers were read from), engine_example (an engine example's pricing block, only when the user explicitly asked to run an example), session (a market previously stored in this session, which itself came from one of the above). There is no value for estimated, recalled or placeholder data. If you would have to invent numbers, do not call this tool: ask the user for the data. preset: a preset with a zero_coupon_bond block (EUR_FIXED_BOND, settlement T+3 on TARGET). maturity_date: YYYY-MM-DD, or tenor counted (by the engine, Unadjusted) from issue_date when given else from as_of. issue_date: YYYY-MM-DD, as_of or omitted (engine: null date). settlement_days, redemption: default from the preset (noted). include_details: pricing.options.bond_pricing_details (duration, convexity).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
as_ofNo
tenorNo
marketYes
presetYes
issue_dateNo
redemptionNo
request_idNo
face_amountYes
maturity_dateNo
include_detailsNo
settlement_daysNo
yield_overridesNo
additional_tradesNo
discounting_curveYes
calendar_overridesNo
market_data_sourceYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.4

TDQS

A3.6/5.0
Behavior3/5

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

No annotations exist, so the description carries the full load. It usefully discloses that settled params default from the preset, how tenor is counted from issue_date/as_of, and that estimated or recalled data is not accepted, but it says nothing about permissions, side effects, determinism, or failure behavior for a POST pricing call.

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 purpose is front-loaded in one line and the remainder is an efficient Args list with no filler. It is appropriately sized for a 16-parameter tool, though the indented bullets are dense enough to be slightly harder to scan than a tighter format.

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?

An output schema exists so return values need not be documented, and the source/guardrail guidance is strong. Still, for a 16-parameter tool with nested objects and 0% schema coverage, leaving required inputs like market and discounting_curve entirely unexplained is a meaningful completeness gap.

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%, so the description has to compensate, and it does explain market_data_source, preset, maturity_date, issue_date, settlement_days/redemption, and include_details. However, two required parameters (market, discounting_curve) and several others (as_of, request_id, additional_trades, yield_overrides, calendar_overrides, face_amount) get no explanation at all.

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?

The opening line gives a precise verb+resource ("Price a zero-coupon bond") plus the underlying endpoint, which is enough for an agent to separate it from the many other bond pricing siblings. It stops short of explicitly contrasting itself with price_fixed_rate_bond or price_floating_rate_bond, so it lands at 4 rather than 5.

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?

The market_data_source enumeration spells out exactly which situations map to which value (pasted, file, engine example, session) and states an explicit exclusion: "If you would have to invent numbers, do not call this tool: ask the user for the data." It gives clear context and a when-not rule, but names no alternative sibling tool, so it misses the top mark.

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