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amend_frozen_application

Destructive

Apply confirmed answer changes to a frozen, pre-submission formation. This supersedes the frozen legal documents and open signature requests, reopens intake, and requires document regeneration and fresh signatures. Use only after the founder explicitly confirms that consequence. Partial data still deep-merges over stored answers. Returns the server-authoritative standardConfiguration with the canonical nextStep. Prerequisite: authenticated active organization access plus every prerequisite stated above. Canonicality: invokes the shared backend action; trust the returned actual_tool_output and context_engineering instead of adding a state-recovery call. Idempotency: obey the tool-specific retry key or guarantee; if none is stated, inspect refreshed state before retrying. Confirmation boundary: obtain fresh, explicit user confirmation before calling.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYes
companyIdNocorply_companies.id (from get_org). Omit it when the org has one company.
_corply_contextNoEcho context_engineering.context_session from the prior Corply result.

TDQS

A4.5/5.0
Behavior5/5

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

Beyond the annotations, the description discloses major effects: it supersedes frozen legal documents, reopens intake, requires regeneration and fresh signatures, deep-merges partial data, and returns server-authoritative output. It also warns against state-recovery calls and addresses idempotency, which is essential for a destructive operation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The core effect is front-loaded, but the latter half contains generic guardrails ('Canonicality', 'Idempotency', 'Confirmation boundary') that could be trimmed or folded into the prerequisites. Still, for a destructive tool, the repetition is not disqualifying.

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

Completeness5/5

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

For a high-stakes destructive mutation with no output schema, the description covers prerequisites, user-confirmation requirements, return shape, canonicality, and idempotency. An agent has enough context to decide whether and how to call it.

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?

With 67% schema coverage, the schema carries most parameter documentation, but the description adds meaningful behavior: 'Partial data still deep-merges over stored answers' clarifies how the main data parameter is applied. This goes beyond the schema's property definitions.

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?

The opening sentence names a specific action ('apply confirmed answer changes') and a precise resource ('frozen, pre-submission formation'), and the second sentence distinguishes it from ordinary save/validate flows by listing the superseding, reopening, and regeneration consequences. This makes the tool's unique role clear without needing to read sibling names.

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 description gives an explicit gate: 'Use only after the founder explicitly confirms that consequence' and repeats it as a confirmation boundary. It does not name alternative tools, but for a destructive action the when-to-use condition is clear.

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

B3.4/5.0
Disambiguation3/5

There is notable overlap among status/read tools (get_company_briefing, get_status, get_org, whoami) and a dense cluster of payment-related tools (request_payment, await_payment, create_payment_project, create_payment_route_draft, etc.). The detailed descriptions help differentiate them, but agents could still misselect when the surface is this large.

Naming Consistency4/5

Tool names overwhelmingly follow a verb_noun snake_case pattern (e.g., create_payment_route_draft, record_operating_event, start_bank_onboarding). Minor exceptions like 'whoami', 'recall', and 'remember' are acceptable single-verb commands, so the naming is highly consistent overall.

Tool Count2/5

At 52 tools, the server far exceeds the 25+ threshold for 'too many'. While the breadth of domains (formation, payments, cap table, operating compliance) somewhat justifies the count, it still feels heavy and likely increases selection errors and cognitive load for agents.

Completeness4/5

The tool surface covers the full formation lifecycle (save, validate, generate, sign, submit), payment handling, bank onboarding, cap table management, and operating records/evidence workflows. Minor gaps exist (e.g., no update/delete for existing companies, no explicit company dissolution), but the core workflows are well covered.