Siren

list_films

Read-onlyIdempotent

The film library, one ranked page at a time. Films sit on job shelves; pass job and the human's goal and hire from the top of the page. Each film says what it is, when to hire it, its length and shapes, fits_this_brand (with what is missing) and made_recently (this brand already got it: prefer another film on the shelf unless the human asked for that one). Page on with next_page. Want it all at once? all=true, or fetch the catalog file (https://api.mysiren.ai/api/v1/films.md, every film by shelf, also .txt/.json) and read it in steps. search= finds films by word. Then describe_film for the body. Video renders need Pro or above. Every film here is 25 credits. Platinum films (50 credits) are not in these pages: the answer's platinum section flags them, and list_platinum_films has the shelf.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`all`	No	true = every film that passes the filters on one page (about 10k tokens for the whole library). Prefer job + page, or the catalog.md file.
`job`	No	The shelf: launch, feature (one feature or update), explain (what the product does), brand (story, manifesto, mood), ai (AI or agent product), proof (a number, testimonials), app (mobile app), shop (products, food, property), people (team or mascot). Omit to rank the whole library.
`goal`	No	The human's own words for the outcome, e.g. "launch video for our new AI agent" or "show our 10k users". Ranks the films by fit.
`page`	No	Page number, from 1. Each page is page_size films; next_page in the answer says what to call next.
`aspect`	No	Only films that render this shape: wide-desktop, square-ig, story-reel, vertical-ig-feed.
`detail`	No	"short" (default) or "full" to add the long description per film.	short
`search`	No	Find films by word across ids, names and descriptions, e.g. "phone", "chat", "mascot", "halftone". Every word must match.
`narrated`	No	true = only films with a voice-over part; false = only music-and-motion films.
`page_size`	No	Films per page, 1 to 25.
`max_seconds`	No	Only films this long or shorter, e.g. 15 for a short feed post.

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

Changed10 schema fields changedSep 24, 2026

addedInput schema / properties / all

Added value: +{
+  "default": false,
+  "description": "true = every film that passes the filters on one page (about 10k tokens for the whole library). Prefer job + page, or the catalog.md file.",
+  "type": "boolean"
+}

addedInput schema / properties / aspect

Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "description": "Only films that render this shape: wide-desktop, square-ig, story-reel, vertical-ig-feed."
+}

addedInput schema / properties / detail

Added value: +{
+  "default": "short",
+  "description": "\"short\" (default) or \"full\" to add the long description per film.",
+  "type": "string"
+}

changedInput schema / properties / goal / description

Previous value: -"Optional: the human's own words for the outcome, e.g. \"tell our story\" or \"launch a feature\". Reorders the catalog by fit."New value: +"The human's own words for the outcome, e.g. \"launch video for our new AI agent\" or \"show our 10k users\". Ranks the films by fit."

addedInput schema / properties / job

Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "description": "The shelf: launch, feature (one feature or update), explain (what the product does), brand (story, manifesto, mood), ai (AI or agent product), proof (a number, testimonials), app (mobile app), shop (products, food, property), people (team or mascot). Omit to rank the whole library."
+}

addedInput schema / properties / max_seconds

Added value: +{
+  "anyOf": [
+    {
+      "type": "number"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "description": "Only films this long or shorter, e.g. 15 for a short feed post."
+}

addedInput schema / properties / narrated

Added value: +{
+  "anyOf": [
+    {
+      "type": "boolean"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "description": "true = only films with a voice-over part; false = only music-and-motion films."
+}

addedInput schema / properties / page

Added value: +{
+  "default": 1,
+  "description": "Page number, from 1. Each page is page_size films; next_page in the answer says what to call next.",
+  "type": "integer"
+}

addedInput schema / properties / page_size

Added value: +{
+  "default": 8,
+  "description": "Films per page, 1 to 25.",
+  "type": "integer"
+}

addedInput schema / properties / search

Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "description": "Find films by word across ids, names and descriptions, e.g. \"phone\", \"chat\", \"mascot\", \"halftone\". Every word must match."
+}

AddedSep 17, 2026

TDQS

A4.8/5.0

Behavior5/5

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

Beyond the readOnlyHint and idempotentHint annotations, the description discloses important behavioral constraints: it is paginated (one ranked page at a time), films are ranked by job/goal fit, every film here is 25 credits, platinum films (50 credits) are excluded, and video renders require Pro or above. It also explains the output structure (each film says what it is, when to hire it, length, shapes, fits_this_brand with missing info, and made_recently). No contradiction with annotations.

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 relatively long but information-dense; each sentence adds a new capability or constraint. It front-loads the core concept (film library, ranked page) and then layers pagination, filters, pricing, and alternative tools. Some metaphorical language ('hire from the top of the page') could be more concise, but it remains efficient and structured. Not verbose enough to be a 3, but not optimal enough for a 5.

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 that the tool has an output schema (though not shown) and annotations for read-only and idempotent, the description covers all essential aspects: pagination mechanics, ranking logic, filters (aspect, search, narrated, max_seconds), all films option, catalog file alternative, credit costs, plan requirements, and pointers to related tools. It leaves nothing critical missing for an agent to call it correctly.

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?

The schema already describes all 10 parameters with 100% coverage, so the baseline is 3. The description adds value by explaining how parameters interact: 'pass job and the human's goal', 'Page on with next_page', 'all=true' for all, and 'search= finds films by word'. It also clarifies the 'job' concept (shelf) and the 'goal' as the human's words. This cross-parameter usage guidance goes beyond the schema and earns a 4.

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 that this tool lists the film library, one ranked page at a time, and that films sit on job shelves, pass job and goal to rank them. It distinguishes itself from sibling tools by explicitly pointing to list_platinum_films for platinum films and describe_film for the body. The verb 'list' and resource 'films' are clear, with a strong metaphor that conveys the ranking and filtering behavior.

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?

The description provides explicit usage instructions: pass job and the human's goal, page on with next_page, use all=true for all films, or fetch the catalog file. It also tells when NOT to use it: for platinum films use list_platinum_films, and for the body of a film use describe_film. It mentions search= for word matching. This gives clear direction on when to use this tool versus its siblings.

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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