Rafe Blandford — career and writing

Map a role's requirements to published evidence

map_role_requirements

Read-onlyIdempotent

Check up to eight requirements of a role against what rafeblandford.com publishes, in one call. Each row is exactly what check_experience returns for that subject: supported, partial or not_found, a statement to pass on, and sources you can check.

⚠️ PASS SUBJECTS, NOT SENTENCES. Break the role into its subjects first — two to four words each, such as 'product strategy', 'engineering leadership', 'retail'. A whole requirement matches nothing and returns not_found even where the site evidences it.

⚠️ THERE IS NO SCORE. The counts describe what this site publishes about the subjects you chose, which is a selection of Rafe's work. Do not turn them into a percentage, a rating or a verdict on fit, and do not turn a not_found into 'Rafe has no experience of X'. LinkedIn is the fuller record and is in every response.

Input Schema

Name	Required	Description	Default
`role`	Yes	The role, as a short title — 'Chief Technology Officer, consumer retail'. Used as the heading; it does not change any row.
`requirements`	Yes	One to eight subjects, two to four words each, in the order to show them. Not the requirement sentences themselves.

Output Schema

Name	Required	Description
`role`	Yes
`rows`	Yes	One check_experience result per requirement, unchanged, in the order given.
`corpus`	No
`counts`	Yes	Rows by status. A description of the site's published evidence for these subjects, NOT a score of the person.
`reading`	Yes	How to read the counts. Pass it on.
`elsewhere`	Yes
`scope_note`	Yes
`long_subjects`	No	Requirements of more than four words. Matching is on whole words, so these may be not_found because of the phrasing; split them into subjects and ask again.
`requirements_checked`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedOct 16, 2026

addedOutput schema / $defs / CheckExperienceOutput / properties / shown_in_the_work

Added value: +{
+  "anyOf": [
+    {
+      "additionalProperties": true,
+      "type": "object"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "description": "Evidence word matching cannot see. Only on partial or not_found. Published work that demonstrates the subject without naming it. Read two or three items and weigh them on what they show, citing them; the status records only the word match.",
+  "title": "Shown In The Work"
+}

AddedOct 16, 2026

TDQS

A4.7/5.0

Behavior5/5

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

Annotations already cover safety (readOnly, idempotent, non-destructive, closed-world), and the description adds substantial context beyond them: the return semantics of each row, that counts are NOT a score or verdict, the not_found misinterpretation trap, and where the fuller record lives. This is exactly the kind of interpretation guidance annotations cannot carry.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loads what the tool does, then layers the two failure modes as flagged warnings. Every sentence either defines behavior or prevents a specific misuse; nothing is padding.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

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 explanation, and annotations cover the safety profile. The description supplies the remaining gaps: failure modes, count interpretation, and the LinkedIn caveat. Nothing an agent needs to call this correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and the schema already documents both parameters, so the baseline is 3. The description goes further by stressing the subject-vs-sentence distinction with concrete examples ('product strategy', 'engineering leadership'), which is the single most likely source of a mangled call, and is worth the extra point.

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

Purpose5/5

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

States a specific verb and resource ('Check up to eight requirements of a role against what rafeblandford.com publishes') plus the key scope constraint ('in one call'). It also distinguishes itself from the sibling check_experience by defining each row as exactly what that tool returns, so an agent can tell them apart without opening either schema.

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?

Gives clear operational guidance on how to use it ('PASS SUBJECTS, NOT SENTENCES', break the role into 2-4 word subjects) and warns about the not_found failure mode. It points to LinkedIn as the fuller record but never explicitly states when to prefer check_experience or get_evidence over this tool for a single requirement, so routing is left partly 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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