Skip to main content
Glama

Deployment Frequency Calculator

deployment-frequency-calculator
Read-onlyIdempotent

Use when a user asks about deployment frequency or DORA deploy cadence.

Input Schema

NameRequiredDescriptionDefault
team_sizeYesteam size used by this deterministic tool.
working_daysNoworking days used by this deterministic tool.
deploys_per_monthYesdeploys per month used by this deterministic tool.

Output Schema

NameRequiredDescriptionDefault
next_stepYes
dora_ratingYes
output_tierYes
signal_valueYes
next_step_urlYes
remaining_pctYes
why_follow_upYes
interpretationYes
deploys_per_dayYes
deploys_per_weekYes
affiliate_contextNo
computation_basisYes
deploys_per_dev_per_dayYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed6 schema fields changed
    • addedInput schema / properties / deploys_per_month / description
      Added value: +"deploys per month used by this deterministic tool."
    • addedInput schema / properties / deploys_per_month / examples
      Added value: +[
      +  1
      +]
    • addedInput schema / properties / team_size / description
      Added value: +"team size used by this deterministic tool."
    • addedInput schema / properties / team_size / examples
      Added value: +[
      +  1
      +]
    • addedInput schema / properties / working_days / description
      Added value: +"working days used by this deterministic tool."
    • addedInput schema / properties / working_days / examples
      Added value: +[
      +  1
      +]
  2. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
      +  "additionalProperties": false,
      +  "properties": {
      +    "affiliate_context": {
      +      "additionalProperties": false,
      +      "properties": {
      +        "affiliate": {
      +          "type": "string"
      +        },
      +        "cta_label": {
      +          "type": "string"
      +        },
      +        "disclosure": {
      +          "type": "string"
      +        },
      +        "framing": {
      +          "type": "string"
      +        },
      +        "posture": {
      +          "enum": [
      +            "secondary"
      +          ],
      +          "type": "string"
      +        },
      +        "slot_id": {
      +          "type": "string"
      +        },
      +        "url": {
      +          "type": "string"
      +        },
      +        "variant": {
      +          "type": "string"
      +        }
      +      },
      +      "required": [
      +        "affiliate",
      +        "cta_label",
      +        "disclosure",
      +        "framing",
      +        "posture",
      +        "slot_id",
      +        "url",
      +        "variant"
      +      ],
      +      "type": "object"
      +    },
      +    "computation_basis": {
      +      "type": "string"
      +    },
      +    "deploys_per_day": {
      +      "type": "number"
      +    },
      +    "deploys_per_dev_per_day": {
      +      "type": "number"
      +    },
      +    "deploys_per_week": {
      +      "type": "number"
      +    },
      +    "dora_rating": {
      +      "type": "string"
      +    },
      +    "interpretation": {
      +      "type": "string"
      +    },
      +    "next_step": {
      +      "type": "string"
      +    },
      +    "next_step_url": {
      +      "type": "string"
      +    },
      +    "output_tier": {
      +      "type": "string"
      +    },
      +    "remaining_pct": {
      +      "type": "number"
      +    },
      +    "signal_value": {
      +      "type": "number"
      +    },
      +    "why_follow_up": {
      +      "type": "string"
      +    }
      +  },
      +  "required": [
      +    "computation_basis",
      +    "deploys_per_day",
      +    "deploys_per_dev_per_day",
      +    "deploys_per_week",
      +    "dora_rating",
      +    "interpretation",
      +    "next_step",
      +    "next_step_url",
      +    "output_tier",
      +    "remaining_pct",
      +    "signal_value",
      +    "why_follow_up"
      +  ],
      +  "type": "object"
      +}
  3. Changed1 schema field changed
    • addedInput schema / additionalProperties
      Added value: +false
  4. First observed

TDQS

B3/5.0
Behavior2/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is fully covered elsewhere. The description adds nothing behavioral on top — no mention of determinism, required inputs, or what the computed result represents — so it contributes almost no value beyond the structured fields.

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?

It is a single short, front-loaded sentence with zero padding, which is structurally clean. But the brevity comes at the cost of substance — this reads as under-specification rather than disciplined conciseness.

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?

An output schema exists and annotations plus 100% schema coverage carry the parameter and safety burden, so the description needn't explain return values. Still, it never states what the calculator produces (e.g., deploys per day per team member), which is the one piece of context the surrounding structured data does not supply.

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 100%, so all three parameters (deploys_per_month, team_size, working_days) are already documented, and the description adds no additional meaning or interaction notes. Baseline 3 applies when the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names the domain ('deployment frequency', 'DORA deploy cadence') but never states a verb or what the tool actually computes, leaving the action to be inferred from the name alone. It also fails to distinguish itself from the sibling dora-metrics-calculator, which plausibly covers the same DORA cadence territory.

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 single sentence is explicitly a routing trigger ('Use when a user asks about deployment frequency or DORA deploy cadence'), which tells an agent the conversational condition for selecting it. However, it offers no when-not condition and does not address the overlapping dora-metrics-calculator sibling.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources