get_researchRead one research theme in full: the opening argument, every chart with its numbers, the findings, the named sources with publisher, sample size, and caveats, and anything still unconfirmed. Cite the source line, not just the chart.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | Research theme slug, e.g. proof-gap or task-fallacy. |
| Name | Required | Description | Default |
|---|---|---|---|
| theme | Yes |
Changes observed during successful MCP inspections.
Output schema / (root)Previous value: -nullNew value: +{
+ "$schema": "http://json-schema.org/draft-07/schema#",
+ "additionalProperties": false,
+ "properties": {
+ "theme": {
+ "additionalProperties": {},
+ "properties": {
+ "charts": {
+ "items": {
+ "additionalProperties": {},
+ "properties": {
+ "data": {
+ "items": {
+ "additionalProperties": {},
+ "properties": {
+ "label": {
+ "type": "string"
+ },
+ "value": {
+ "type": "number"
+ }
+ },
+ "required": [
+ "label",
+ "value"
+ ],
+ "type": "object"
+ },
+ "type": "array"
+ },
+ "headline": {
+ "type": "string"
+ },
+ "id": {
+ "type": "string"
+ },
+ "source": {},
+ "sub": {
+ "type": "string"
+ },
+ "unit": {
+ "type": "string"
+ }
+ },
+ "required": [
+ "id",
+ "headline",
+ "sub",
+ "unit",
+ "data",
+ "source"
+ ],
+ "type": "object"
+ },
+ "type": "array"
+ },
+ "dek": {
+ "type": "string"
+ },
+ "intro": {
+ "items": {
+ "type": "string"
+ },
+ "type": "array"
+ },
+ "number": {
+ "type": "number"
+ },
+ "shortAnswer": {
+ "type": "string"
+ },
+ "slug": {
+ "type": "string"
+ },
+ "sources": {
+ "items": {
+ "additionalProperties": {},
+ "properties": {
+ "detail": {
+ "type": "string"
+ },
+ "name": {
+ "type": "string"
+ },
+ "url": {
+ "type": "string"
+ }
+ },
+ "required": [
+ "name",
+ "detail",
+ "url"
+ ],
+ "type": "object"
+ },
+ "type": "array"
+ },
+ "takeaways": {
+ "items": {
+ "type": "string"
+ },
+ "type": "array"
+ },
+ "title": {
+ "type": "string"
+ },
+ "unconfirmed": {
+ "items": {
+ "type": "string"
+ },
+ "type": "array"
+ },
+ "url": {
+ "type": "string"
+ }
+ },
+ "required": [
+ "slug",
+ "number",
+ "title",
+ "dek",
+ "shortAnswer",
+ "intro",
+ "charts",
+ "takeaways",
+ "sources",
+ "unconfirmed",
+ "url"
+ ],
+ "type": "object"
+ }
+ },
+ "required": [
+ "theme"
+ ],
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description goes well beyond the annotations by disclosing the full payload contents: charts with numbers, named sources with publisher and sample size, caveats, and unconfirmed material. It also adds a specific behavioral instruction to cite the source line rather than just the chart, which is valuable context not present in annotations or schema.
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 description is a single, front-loaded sentence that begins with the core action and then efficiently lists the contents of the full theme. Every phrase adds meaningful detail, and there is no filler or repetition of the tool name or annotations.
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?
Given the single required parameter, full schema coverage, an output schema, and read-only/idempotent annotations, the description covers everything needed to call and interpret the tool correctly. The only use-case nuance is routing to list_research for summaries, but that is not necessary for correctness since list_research is clearly a different sibling tool.
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?
The schema already fully documents the only parameter, slug, with examples and a clear description. The tool description adds the context that this slug identifies a 'research theme', but it does not add new parameter-level meaning beyond what the schema provides. With 100% schema coverage, the baseline of 3 is appropriate.
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 starts with 'Read one research theme in full' and then enumerates exactly what is included: opening argument, charts, findings, sources, caveats, and unconfirmed items. This clearly identifies the specific verb, resource, and scope, and distinguishes it from siblings like get_dataset or list_research.
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 makes clear this is for reading a single research theme in full, which implies use when complete detail is needed. It does not explicitly mention alternatives like list_research for overviews or search_publications for finding publications, so it lacks explicit exclusions, but the usage context is clear enough for an agent to select it appropriately.
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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