Read today's D0 cohort; channel_pid required
| Name | Required | Description | Default |
|---|---|---|---|
| today | No | ||
| event_keys | No | ||
| channel_pid | Yes | ||
| product_ref | No | ||
| product_name | No |
| Name | Required | Description | Default |
|---|---|---|---|
| message | No | ||
| retryable | No | ||
| support_ref | No |
Changes observed during successful MCP inspections.
Output schema / $defs / saAdded value: +{
+ "properties": {
+ "can_report_stored_total": {
+ "type": "boolean"
+ },
+ "reason": {
+ "type": "string"
+ },
+ "zero_proven": {
+ "type": "boolean"
+ }
+ },
+ "required": [
+ "can_report_stored_total",
+ "zero_proven",
+ "reason"
+ ],
+ "type": "object"
+}Output schema / else / properties / read_evidenceAdded value: +{
+ "description": "Proofs apply independently to returned metrics and scope as stored/observed. A new read_ref is a call identifier, never a source watermark. False or missing proof means unknown, not zero. Fingerprints correlate requests/results in audits; they are not authorization or pagination tokens.",
+ "properties": {
+ "artifact_returned": {
+ "type": "boolean"
+ },
+ "configuration": {
+ "properties": {
+ "account_inventory_enumerated": {
+ "const": false
+ },
+ "all_campaigns_paused_proven": {
+ "const": false
+ },
+ "requested_ids_complete": {
+ "type": "boolean"
+ },
+ "scope": {
+ "const": "requested_entity_ids_only"
+ }
+ },
+ "type": "object"
+ },
+ "mmp": {
+ "properties": {
+ "can_report_scoped_totals": {
+ "type": "boolean"
+ },
+ "provider_cache_max_age_seconds": {
+ "const": 90
+ },
+ "reason": {
+ "type": "string"
+ },
+ "scope": {
+ "const": "linked_apps_queried_channels_and_windows"
+ },
+ "source_observed_at": {
+ "type": "null"
+ }
+ },
+ "type": "object"
+ },
+ "read_ref": {
+ "pattern": "^read_[0-9a-f]{32}$",
+ "type": "string"
+ },
+ "request_fingerprint": {
+ "type": "string"
+ },
+ "result_fingerprint": {
+ "type": "string"
+ },
+ "scopes": {
+ "items": {
+ "properties": {
+ "all_campaigns_paused_proven": {
+ "const": false
+ },
+ "funnel": {
+ "additionalProperties": {
+ "$ref": "#/$defs/sa"
+ },
+ "maxProperties": 32,
+ "type": "object"
+ },
+ "index": {
+ "type": "integer"
+ },
+ "inventory_anchor": {
+ "type": [
+ "string",
+ "null"
+ ]
+ },
+ "inventory_coverage": {
+ "type": "string"
+ },
+ "inventory_source_observed_at": {
+ "type": [
+ "string",
+ "null"
+ ]
+ },
+ "metrics": {
+ "additionalProperties": {
+ "$ref": "#/$defs/sa"
+ },
+ "type": "object"
+ },
+ "metrics_source_observed_at": {
+ "type": [
+ "string",
+ "null"
+ ]
+ },
+ "range_complete": {
+ "type": [
+ "boolean",
+ "null"
+ ]
+ },
+ "scope": {
+ "const": "stored_query"
+ }
+ },
+ "type": "object"
+ },
+ "maxItems": 10,
+ "type": "array"
+ }
+ },
+ "required": [
+ "read_ref",
+ "request_fingerprint",
+ "result_fingerprint"
+ ],
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=false, so the safety profile is covered. The description adds nothing beyond restating the read operation: it doesn't disclose whether data is cached, whether there are rate limits, what 'today' means relative to timezone, or what the response contains even though an output schema exists.
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 entire description is a single short sentence ('Read today's D0 cohort; channel_pid required'). It is front-loaded and wastes no words, though it is arguably under-specified rather than concise.
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 5-parameter tool with 0% schema coverage and no sibling differentiation, the description is severely incomplete. An agent cannot determine what 'D0 cohort' means, how the parameters behave, or when to choose this tool over similar mmp_insights siblings.
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 0%, so the description must compensate. It only mentions channel_pid being required, leaving today, event_keys, product_ref, and product_name completely undocumented. This is far from adequate for a 5-parameter tool with zero schema descriptions.
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?
The description states 'Read today's D0 cohort', which gives a verb (read) and a resource (today's D0 cohort). However, 'D0 cohort' is domain jargon that is never explained, and there is no differentiation from siblings like mmp_insights_query_product_cohort or mmp_insights_get_product_event_today, which sound extremely similar.
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?
The description notes 'channel_pid required' but gives no guidance on when to use this versus the many other mmp_insights_* tools. There is no mention of prerequisites, alternatives, or scenarios that select this tool.
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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