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Analytics Legends — SAP Analytics Intelligence

List the deep-research studies (metadata only)

list_studies
Read-onlyIdempotent

List the Analytics Legends deep-research studies with their edition, as-of date, audience, word count and canonical URL. METADATA ONLY: study bodies are a paid Consultant-tier deliverable, served by get_study on this same endpoint with a subscriber key. Use this to tell a reader that a study exists and where to read it. ONE ROW IS ONE LANGUAGE EDITION, NOT ONE STUDY: each study is published in every language it has been translated into, so _meta.tranche_total_row_count counts editions and _meta.distinct_studies counts the works. _meta.available_languages gives the live per-language counts; each row carries its editions list. Pass lang to get one row per study.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
langNoISO-639-1 language of the EDITION to list, e.g. en, fr or de — each study is published as one row per language. Omit it to see every edition of every study; the live list of languages actually present comes back as `_meta.available_languages` on every response. A well-formed code the corpus does not hold returns 0 rows.
limitNoMax rows (hard cap 50).
queryNoFree-text filter, case-insensitive. EVERY word must appear in the record (substring per word, any order), so a natural-language phrase narrows the answer instead of having to match verbatim.
cursorNoOpaque token from a previous response's `_meta.next_cursor`. Pass it back with the SAME filter arguments; `null` means the last page. Changing a filter refuses the cursor.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
rowsYes
toolYes
_metaNo
_attributionYes
result_countYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changed
    • changedInput schema / properties / lang / description
      Previous value: -"Language code, EN or FR."New value: +"ISO-639-1 language of the EDITION to list, e.g. en, fr or de — each study is published as one row per language. Omit it to see every edition of every study; the live list of languages actually present comes back as `_meta.available_languages` on every response. A well-formed code the corpus does not hold returns 0 rows."
    • addedOutput schema / properties / rows / items / properties / editions
      Added value: +{
      +  "items": {
      +    "type": "string"
      +  },
      +  "type": [
      +    "array",
      +    "null"
      +  ]
      +}
    • addedOutput schema / properties / rows / items / properties / lang
      Added value: +{
      +  "type": [
      +    "string",
      +    "null"
      +  ]
      +}
  2. Changed1 schema field changed
    • changedInput schema / properties / query / description
      Previous value: -"Free-text filter, matched case-insensitively."New value: +"Free-text filter, case-insensitive. EVERY word must appear in the record (substring per word, any order), so a natural-language phrase narrows the answer instead of having to match verbatim."
  3. Changed1 schema field changed
    • changedInput schema / properties / cursor / description
      Previous value: -"Opaque token from a previous response's `_meta.next_cursor`. Pass it back with the SAME filter arguments to read the next page; a null `next_cursor` means you have reached the end. It is bound to those filters and refused if they change — a cursor names a POSITION in one ordering, and applying it to another query would start the page in the wrong place."New value: +"Opaque token from a previous response's `_meta.next_cursor`. Pass it back with the SAME filter arguments; `null` means the last page. Changing a filter refuses the cursor."
  4. Changed1 schema field changed
    • addedInput schema / properties / cursor
      Added value: +{
      +  "description": "Opaque token from a previous response's `_meta.next_cursor`. Pass it back with the SAME filter arguments to read the next page; a null `next_cursor` means you have reached the end. It is bound to those filters and refused if they change — a cursor names a POSITION in one ordering, and applying it to another query would start the page in the wrong place.",
      +  "maxLength": 512,
      +  "type": "string"
      +}
  5. Changed6 schema fields changed
    • changedOutput schema / properties / rows / items / properties / access / type
      Previous value: -"string"New value: +[
      +  "string",
      +  "null"
      +]
    • changedOutput schema / properties / rows / items / properties / as_of / type
      Previous value: -"string"New value: +[
      +  "string",
      +  "null"
      +]
    • removedOutput schema / properties / rows / items / properties / citation_note
      Removed value: -{
      -  "type": "string"
      -}
    • changedOutput schema / properties / rows / items / properties / slug / type
      Previous value: -"string"New value: +[
      +  "string",
      +  "null"
      +]
    • changedOutput schema / properties / rows / items / properties / title / type
      Previous value: -"string"New value: +[
      +  "string",
      +  "null"
      +]
    • changedOutput schema / properties / rows / items / properties / word_count / type
      Previous value: -"integer"New value: +[
      +  "integer",
      +  "null"
      +]
  6. Changed3 schema fields changed
    • addedOutput schema / properties / rows / items / properties / citation_note
      Added value: +{
      +  "type": "string"
      +}
    • addedOutput schema / properties / rows / items / properties / citation_scope
      Added value: +{
      +  "enum": [
      +    "record",
      +    "section_hub"
      +  ],
      +  "type": "string"
      +}
    • addedOutput schema / properties / rows / items / properties / citation_url
      Added value: +{
      +  "type": "string"
      +}
  7. First observed

TDQS

A4.8/5.0
Behavior5/5

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

The description discloses read-only behavior, the one-row-per-language-edition semantics, the `_meta` fields, and the outcome for invalid language codes (0 rows). These details go beyond the annotations and do not contradict `readOnlyHint`, `idempotentHint`, or `destructiveHint`.

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?

The description is dense and front-loaded with the purpose, but it repeats the language-edition rule twice ('ONE ROW IS ONE LANGUAGE EDITION' and later 'each row carries its editions list'). This minor redundancy prevents a perfect score.

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?

Given the presence of an output schema, the description appropriately omits return-value details but includes essential operational context: metadata-only nature, pagination, `_meta` fields, and the relationship to `get_study`. It is complete for the intended use.

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 descriptions fully cover all four parameters, so the baseline is 3. The description adds value by reinforcing the meaning of `lang` (one row per language) and the cursor's dependency on unchanged filters, giving extra context beyond the schema.

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?

The description clearly states the tool's function: listing deep-research studies with metadata fields (edition, as-of date, audience, word count, URL). It explicitly contrasts with `get_study` for study bodies, making its scope distinct from sibling tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It plainly says 'METADATA ONLY,' directs to `get_study` for bodies, and explains the use case ('tell a reader that a study exists and where to read it'). It also covers pagination, language-edition behavior, and filter constraints, leaving no ambiguity about when and how to use it.

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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