get_user_by_emailRetrieves a single user by exact normalized email address, using case-insensitive matching, to look up CRM users from their email.
Get User by Email.
Retrieves a single user by normalised exact email match. Email matching is case-insensitive after normalisation.
| Name | Required | Description | Default |
|---|---|---|---|
| Yes | The email address to search for. |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already declare readOnlyHint, idempotentHint, openWorldHint, and destructiveHint=false, so the safety profile is fully covered elsewhere. The description's added value is the matching semantics: exact match after normalisation, case-insensitive — a genuinely useful detail. It stops short of disclosing what happens on zero matches (null, empty, or error) or whether multiple users could collide under normalisation, which would matter for a single-result tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The opening line merely restates the title and could be dropped, but the two following sentences are tight and front-load the key constraint (exact, normalised, case-insensitive matching). No filler or marketing language.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter read tool with full schema coverage and rich annotations, this is close to complete — the agent knows the key type, matching behaviour, and that the call is safe and idempotent. The one meaningful omission is the not-found result shape, which matters since there is no output schema to describe it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and the email parameter already carries a description, format, and validation pattern, so the baseline is 3. The description does add interpretation beyond the schema by clarifying that the supplied address is normalised and compared case-insensitively, but it does not define the normalisation rules themselves.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb and resource ('Retrieves a single user') and narrows the lookup key to an exact email match, which separates it from get_user and list_users at a glance. It does not explicitly name those siblings, but the 'by email' qualifier carries the differentiation on its own.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is only implied: an agent can infer this is the tool for email-based user lookup rather than ID-based or list-based lookup. There is no explicit guidance on when to prefer it over get_user or list_users, and no mention of fallback behaviour when no match exists.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.