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by io.engineeringleaders
OverviewDiscussionsAdmin

Benchmark your manager-to-senior-IC ratio

benchmark_leadership_ratio
Read-onlyIdempotent

Answers 'what shape is my engineering org, and what should I ask about it?' Returns your manager-versus-senior-IC percentages and the resulting span (1 manager per N senior ICs), plus the question that shape usually raises. ELC's own community composition is shown alongside as context only — different denominator, so no delta and no score is computed against it.

Input Schema

NameRequiredDescriptionDefault
contextYesExplain why you are calling this tool and how it fits into the user's overall goal. This parameter is used for analytics and user intent tracking. YOU MUST provide 15-25 words (count carefully). NEVER use first person ('I', 'we', 'you') - maintain third-person perspective. NEVER include sensitive information such as credentials, passwords, or personal data. Example (20 words): "Searching across the organization's repositories to find all open issues related to performance complaints and latency issues for team prioritization."
managersNoRequired. Managers and tech leads.
senior_icsNoRequired. Senior and staff ICs. Leave out junior and mid ICs on both sides.

Output Schema

NameRequiredDescriptionDefault
dataNoMachine-readable payload; this is what `signature` covers.
reportYesThe full human-readable report.
sourceYesCanonical engineeringleaders.io page this answer derives from.
verdictNoHeadline verdict, when the tool returns one.
signatureNoDetached JWS (RFC 7797) over the JCS-canonical form of `data`; verify against jwks_url.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • addedOutput schema / properties / data
      Added value: +{
+  "additionalProperties": {},
+  "description": "Machine-readable payload; this is what `signature` covers.",
+  "propertyNames": {
+    "type": "string"
+  },
+  "type": "object"
+}
    • addedOutput schema / properties / signature
      Added value: +{
+  "additionalProperties": false,
+  "description": "Detached JWS (RFC 7797) over the JCS-canonical form of `data`; verify against jwks_url.",
+  "properties": {
+    "jwks_url": {
+      "type": "string"
+    },
+    "jws": {
+      "type": "string"
+    },
+    "kid": {
+      "type": "string"
+    },
+    "signed": {
+      "const": "data",
+      "type": "string"
+    }
+  },
+  "required": [
+    "jws",
+    "kid",
+    "jwks_url",
+    "signed"
+  ],
+  "type": "object"
+}
  2. Changed3 schema fields changed
    • changedInput schema / properties / managers / description
      Previous value: -"Managers and tech leads."New value: +"Required. Managers and tech leads."
    • changedInput schema / properties / senior_ics / description
      Previous value: -"Senior and staff ICs. Leave out junior and mid ICs on both sides."New value: +"Required. Senior and staff ICs. Leave out junior and mid ICs on both sides."
    • changedInput schema / required
      Previous value: -[
-  "managers",
-  "senior_ics",
-  "context"
-]New value: +[
+  "context"
+]
  3. 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 readOnly, idempotent, non-destructive, closed-world, so the safety profile is covered. The description adds genuinely non-obvious behavior: ELC community composition is context only, uses a different denominator, and produces no delta or score. That preempts an agent misreading the comparison as a scorecard.

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 question the tool answers, then the returned values. The em-dash aside about the ELC denominator is dense but earns its place by preventing a misreading. Slightly clause-heavy phrasing keeps it off a 5.

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?

An output schema exists, so return values need no elaboration, and the tool itself takes only two substantive numeric inputs. The description covers purpose, output shape, and the key caveat about the external benchmark. What is missing is input-side guidance (e.g. whether zero managers is valid) and the required/optional discrepancy.

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 the baseline is 3 and the schema already spells out managers, senior_ics, and the heavily-constrained context field. The description adds nothing about inputs, and notably does not resolve the ambiguity that the schema marks managers/senior_ics as 'Required' in their descriptions while only 'context' appears in the top-level required array.

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 names a concrete computation (manager-vs-senior-IC percentages, span = 1 manager per N senior ICs) and the question it answers, so an agent can predict its output. It is distinguishable from every sibling, none of which benchmark org composition. It stops short of stating the derivation from the managers/senior_ics inputs in a single crisp verb+resource sentence.

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?

The framing question ('what shape is my engineering org, and what should I ask about it?') implies the usage context, but there is no explicit when-to-call, when-not-to-call, or named alternative among the siblings. The only boundary drawn is against the external ELC benchmark ('no delta and no score is computed against it'), which is a scope caveat rather than 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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