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TechFiyr AI-Native Software Agency

request_quote

Evaluates a software specification against TechFiyr programmatic guardrails and pricing matrix, returning a formal quote ID, breakdown, SLA tier (7-day or 14-day), and milestones.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "description": "<description>"
    },
    "name": "request_quote"
  }
}

Input Schema

NameRequiredDescriptionDefault
platformNo
budgetUSDNoBuyer agent budget ceiling in USD.
techStackNoRequested technologies (e.g. Next.js, Java Spring, Python, PHP/Laravel, Flutter, React Native, Capacitor, Android, iOS, ERP/HR, AI Try-On).
clientEmailNo
descriptionYesFunctional specification and requirements.
crudEntitiesNoEstimated database/CRUD entities (max 5 for 7-day SLA).
projectTitleNoShort name of the application or platform.
clientAgentIdNo
mobileScreensNoEstimated mobile screens (max 4 for 7-day SLA).
requestedDaysNoDesired turnaround in days (minimum 7).
integrationsCountNoExternal API/payment/auth integrations (max 3 for 7-day SLA).
paymentPreferenceNo
requiresCustomAiTrainingNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • changedInput schema / properties / platform / enum
      Previous value: -[
      -  "web",
      -  "mobile",
      -  "fullstack",
      -  "ai",
      -  "design"
      -]New value: +[
      +  "web",
      +  "mobile",
      +  "fullstack",
      +  "ai",
      +  "design",
      +  "enterprise"
      +]
    • changedInput schema / properties / techStack / description
      Previous value: -"Requested technologies (e.g. Next.js, PostgreSQL, Flutter)."New value: +"Requested technologies (e.g. Next.js, Java Spring, Python, PHP/Laravel, Flutter, React Native, Capacitor, Android, iOS, ERP/HR, AI Try-On)."
  2. First observed

TDQS

B3.2/5.0
Behavior3/5

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

No annotations are supplied, so the description carries the full behavioral burden. It does disclose useful context — evaluation happens against guardrails and a pricing matrix, and the SLA tier is either 7-day or 14-day — but it never says whether the quote is binding or expires, what happens when a spec violates a guardrail, or whether issuing a quote creates persistent state. Those are meaningful gaps for a no-annotation tool.

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?

A single front-loaded sentence that moves from the action to the evaluation basis to the returned artifacts with no filler. It is tight, though the output list is packed densely enough that it reads as a run-on.

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 13 parameters and no output schema, the description usefully enumerates the return values (quote ID, breakdown, SLA tier, milestones), which compensates for the missing output schema. What remains incomplete is failure behavior and the trade-off logic linking the schema's SLA caps to the returned tier, but the core call contract is covered.

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 coverage is 62% across 13 parameters, with the schema itself documenting budgetUSD, techStack, crudEntities, mobileScreens, requestedDays, and integrationsCount, including the 7-day SLA caps. The description adds no parameter-level meaning or constraint explanation beyond what the schema already states, so it sits at the baseline for partial coverage.

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 gives a specific verb ('Evaluates') and resource ('a software specification against TechFiyr programmatic guardrails and pricing matrix') and lists the concrete return artifacts (quote ID, breakdown, SLA tier, milestones). Siblings like submit_project_spec and negotiate_terms are never named or contrasted, so sibling differentiation is left to inference.

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?

There is no explicit when-to-use guidance, no prerequisites, and no statement of when to prefer this over submit_project_spec or negotiate_terms. An agent can infer it produces a price quote, but nothing tells it which stage of the workflow this belongs to.

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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