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Niche — Editorial Intelligence

by com.nicheangle

Export a session

niche_session_export
Read-only

Export a session as a structured calendar artifact preserving session_id and per-story story_id traceability. Use after a niche_signal_scan when you want a metadata-rich content backlog instead of running individual pieces end-to-end. Outputs a standard editorial-calendar shape suitable for content-backlog and planning workflows.

Two formats: • markdown: human-readable and agent-citable. Session metadata at top (session_id, niche, scan timestamp, and brand_profile_active state). Then a card per story with title, headline_candidate, summary, recency_score, publication_breakdown, source_breakdown, and empty slots for the user to fill (Frame, Hook, Article-shape, Ship Order). Followed by a 'recommended ship order' section and cross-cutting notes. • json: structured shape ready to pipe to other tools or load into a notebook. Same data, machine-shaped.

Preserves story_id and session_id traceability so you can come back in N weeks and re-run niche_angle_propose / niche_draft_create against the same stories with the same brand profile bound. The artifact is the entry point to a calendar-builder workflow.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
formatNoOutput shape. Default markdown.markdown
session_idYes

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so safety is covered. The description adds details about output formats (markdown vs. json), what each contains, and that it preserves session_id/story_id traceability, providing value beyond the 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 detailed but well-structured: opening purpose, usage guidance, two bullet-point formats, and a traceability paragraph. Every sentence earns its place, though the format bullets are somewhat verbose. Still within reason for a tool with complex output shapes.

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?

With no output schema, the description thoroughly explains what the tool returns (content of markdown and json exports, traceability, and workflow fit). It also covers when to use it, making the description near-complete for an export tool with only two parameters.

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 covers format with enum/default but not session_id. The description adds substantial detail about both formats (markdown human-readable vs. json machine-shaped) and the artifact's content, compensating for the 50% schema coverage. It doesn't elaborate on session_id, but that is self-explanatory.

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 states 'Export a session as a structured calendar artifact' with a specific verb, resource, and output type. It distinguishes from siblings like niche_list_sessions and niche_signal_scan by emphasizing the structured backlog artifact and workflow integration.

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 explicitly says 'Use after a niche_signal_scan when you want a metadata-rich content backlog instead of running individual pieces end-to-end.' This gives clear when-to-use context and an implicit alternative, making it easy for an agent to choose correctly.

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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TDQS

A4.2/5.0
Disambiguation4/5

Tools are mostly distinct across the pipeline—discovery, brand setup, drafting, rendering, publishing, session management—and descriptions are detailed. Minor overlap exists between niche_signal_scan and niche_intelligence_query (both discovery) and between niche_add_output and niche_draft_create (both generate outputs), but the descriptions clearly differentiate them. Overall, an agent can reliably select the right tool.

Naming Consistency3/5

All tools share the `niche_` prefix and snake_case, but the verb/noun order is inconsistent: some are verb-first (add_output, render_image_card, list_sessions) while many are noun-first (angle_propose, brand_kit_ingest, draft_create, session_cancel). This mixed convention requires the agent to learn each name individually rather than predict the pattern.

Tool Count3/5

25 tools is on the heavy side but appropriate for the platform's scope—full editorial intelligence from discovery to publish. No redundant tools, and each covers a distinct aspect, but the count is high enough that it feels dense and may require orientation (which niche_whoami addresses).

Completeness4/5

The toolset covers the full workflow: discovery, angle proposal, drafting, revision, publishing, rendering, asset attachment, brand setup, and session management. Minor gaps exist, such as no direct read tool for the current BrandKit (only via ingest status) and no hard-delete tool (session_cancel mentions the REST endpoint instead), but these are edge cases and agents can work around them.

Resources