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Mode VC: AI Venture Research Charts & Investor Atlas

Fundraising Readiness: Data Room Score, Runway and Burn Multiple

calc_fundraising_readiness
Read-onlyIdempotent

Scores diligence readiness from a weighted 12-item data room checklist (overall, Corporate and Legal, and each pillar), and computes runway and burn multiple from cash, burn and ARR growth. Same scoring as https://modevc.com/tools/fundraising-readiness. The investor-update email draft on that page is not included.

Input Schema

NameRequiredDescriptionDefault
arrNoARR in USD. Web default 780,000.
cashNoCash in the bank in USD. Web default 1,450,000.
raise_targetNoRaise target in USD (echoed, not used in the score). Web default 3,500,000.
mom_growth_pctNoMonth over month ARR growth in percent. Web default 18.
documents_readyNoChecklist items that are ready. Omit to use the web calculator example (all except valuation_409a, retention_cohorts, architecture_and_security). Pass [] for none.
monthly_net_burnNoMonthly net burn in USD. Web default 65,000.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already declare readOnly, idempotent, non-destructive, closed-world behavior, so the safety profile is covered. The description adds the scoring basis (weighted 12-item checklist) and clarifies the excluded email draft, but says nothing about return shape or edge-case handling.

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?

Three front-loaded sentences with minimal waste: purpose first, then provenance and exclusion. The email-draft exclusion sentence is a useful boundary even if slightly expendable.

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 no output schema, the description helpfully enumerates the outputs (overall, Corporate and Legal, each pillar, runway, burn multiple). It is complete enough that an agent can call it and interpret results, though exact return fields remain unspecified.

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 100%, so the schema already documents all six parameters including web defaults and the omit-vs-empty-list behavior. The description adds no parameter-level meaning beyond that, so 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+resource: scores diligence readiness from a weighted 12-item data room checklist and computes runway and burn multiple. Clear, but it overlaps with the sibling calc_burn_multiple_runway without distinguishing itself from it.

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 explicit when-to-use guidance and no alternatives named, despite a sibling (calc_burn_multiple_runway) that also computes runway and burn multiple. The only scope note is that the email draft is excluded, which is not usage guidance.

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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