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EPIC scores (in Claude)

epic_audit
Read-only

Get EPIC framework scores for your GTM strategy: Ecosystem and ABM, Product-Led Growth, Inbound and Outbound, Community-Led, each 1 to 10, with the lead motion, warnings and notes, and the sector's buying committee and usual objections when your inputs name the sector. Add the optional inputs for a full score; without them the result is marked preliminary.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
acv_usdNoOptional. Average contract value per year in US dollars (for example 42000)
industryNoYour industry
challengeYesDescribe your GTM situation
geographyNoOptional. Primary market
self_serveNoOptional. true if customers can sign up and get value without talking to sales
deal_sourceNoOptional. Where the majority of deals come from
nrr_percentNoOptional. Net revenue retention in percent (for example 108)
company_nameNoOptional. Your company or product name, repeated in the answer
tam_accountsNoOptional. Number of addressable accounts (for example 2500)
business_stageNoStage: pre-seed, seed, series-a, series-b, series-c, bootstrapped (growth counts as Series B)
deal_cycle_daysNoOptional. Days from first touch to closed-won (for example 120)
current_channelsNoOptional. What you do today (content, outbound, events, partnerships, PLG, community)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=false, so safety is covered. The description adds genuinely new behavior: results are downgraded to "preliminary" when optional inputs are omitted, and it discloses what the response contains (lead motion, warnings/notes, buying committee, objections). No auth or rate-limit details, but those are not required for a read-only computation.

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?

Two sentences, front-loaded with the return contents and followed by the conditional-full-score rule. The first sentence is long and list-heavy but every clause describes a distinct part of the output, so little is wasted.

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 12 parameters, 1 required, and no output schema, the description carries the burden of describing return values, which it does (scores, lead motion, warnings, notes, buying committee, objections). It is nearly complete; only the preliminary-vs-full distinction's effect on specific fields could be spelled out more.

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 baseline is 3 and the schema already documents every parameter including enums and examples. The description adds only a collective reference to "optional inputs" and notes that naming the sector triggers buying-committee/objections output, but no per-parameter syntax or format detail 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?

Names a specific verb (get) and resource (EPIC framework scores) and enumerates the four motions returned (Ecosystem/ABM, PLG, Inbound/Outbound, Community-Led, each 1-10). It is clearly distinguishable from siblings like generate_roadmap or gtm_consultation by being a scoring/audit tool, though it never names those alternatives directly.

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?

States a usage condition for the optional inputs ("Add the optional inputs for a full score; without them the result is marked preliminary"), which is helpful. However, it gives no guidance on when to prefer this over gtm_consultation or generate_roadmap, leaving tool selection to inference.

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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