Cofferline

create_pm_order

Place a prediction-market limit order under policy, signed server-side with the stored credential. Polymarket: condition_id, token_id, action, price_usd (e.g. '0.55'), size_shares. Auth required.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`state`	No	optional current exposure: {market_exposure_usd, realized_loss_today_usd, total_open_exposure_usd} as decimal strings
`venue`	No	prediction-market venue (default polymarket)	polymarket
`action`	Yes
`wallet`	Yes	treasury wallet whose policy governs the order
`token_id`	No	Polymarket: outcome token id, decimal string
`price_usd`	No	Polymarket: limit price, '0.xx'
`size_shares`	No	Polymarket: share count, decimal string
`condition_id`	No	Polymarket: market condition id
`credential_id`	Yes	stored credential id (uuid)
`client_order_id`	No	optional idempotency uuid

TDQS

B3.4/5.0

Behavior3/5

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

With no annotations provided, the description must disclose behavioral traits. It states that orders are signed server-side with a stored credential and that auth is required, which provides some context. However, it omits potential side effects like irreversible order placement, fee implications, or policy enforcement specifics.

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, front-loaded with the core action and policy context. The second sentence efficiently enumerates key parameters without redundancy. No wasted words.

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?

Although there is no output schema, the tool is a create operation with 10 parameters. The description covers the main purpose and key parameters but omits the `state` and `client_order_id` semantics. Given the schema descriptions are thorough, the description is adequate but not exhaustive, leaving room for the agent to infer defaults and optional fields.

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

Parameters4/5

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

Schema description coverage is 90%, so baseline is 3. The description adds value by highlighting Polymarket-specific fields and giving a concrete example of the price format ('0.55'). It also lists the essential parameters in sequence, which helps the agent understand the minimum required fields beyond the schema.

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 description clearly states the tool places a prediction-market limit order, with specific details about server-side signing and policy constraints. It distinguishes from sibling tools like prepare_pm_order and submit_pm_order by mentioning the 'under policy' and server-side signing aspects, though it doesn't explicitly contrast with them.

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?

No guidance is given on when to use this tool versus alternatives like submit_pm_order or prepare_pm_order. It mentions 'under policy' but doesn't explain the intended flow (e.g., prepare then submit) or exclusions.

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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TDQS

A3.8/5.0

Disambiguation5/5

Each tool targets a distinct resource and action. Within the prediction market domain, prepare vs create vs submit are clearly differentiated by signing model (client-signed vs server-signed). Even similar-sounding tools like check_spend and check_pm_order are unambiguously scoped to general spending vs PM orders, and their descriptions reinforce the boundary.

Naming Consistency5/5

All 47 tools follow a consistent verb_noun pattern with lowercase snake_case. Verbs like get, list, create, cancel, revoke, prepare, submit, set, remove, and poll are used uniformly. There is no mixing of styles or vague verbs like 'process' or 'run', making the surface highly predictable.

Tool Count2/5

47 tools is significantly above the 25-tool threshold for 'too many'. While the server covers a broad and complex domain (prediction markets, policy, delegations), the sheer count makes the surface heavy and potentially overwhelming. Some consolidation (e.g., merging related PM order operations) could reduce cognitive load without sacrificing functionality.

Completeness4/5

The tool set provides comprehensive lifecycle coverage across all major subdomains: authentication, policy versioning, delegation CRUD (prepare/confirm/list/get/revoke/renew), intent management, PM order flow (create/cancel/list/prepare/submit/check), credential management (store/list/revoke), balance and top-up operations, and account-level actions (export, offboard, panic). Minor omissions exist (e.g., no dedicated tool to view a single credential in detail or update an intent), but agents can work around these with existing tools.

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