commentary
Public-domain, attributed commentary (Matthew Henry) on a reference — the commentator's own words, found and cited, never generated.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| ref | Yes | ||
| source | No |
Public-domain, attributed commentary (Matthew Henry) on a reference — the commentator's own words, found and cited, never generated.
| Name | Required | Description | Default |
|---|---|---|---|
| ref | Yes | ||
| source | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description provides useful behavioral context by stating the commentary is 'found and cited, never generated', which clarifies that the tool retrieves existing text rather than synthesizing new content. With no annotations, it conveys the core read-only nature but lacks details on return format, error handling, or permissions.
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, well-structured sentence that front-loads the key information (public-domain, attributed, Matthew Henry) and every clause adds value. No wasted words.
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 simple two-parameter read tool, the description provides sufficient context to understand the core behavior and source. The main gap is the unexplained 'source' parameter and lack of explicit return-value description, but the purpose is clear enough.
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 clarifies that 'ref' is a reference, but the optional 'source' parameter is completely unexplained. The description adds partial meaning for the primary parameter but not enough to fully cover both.
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 clearly identifies the tool's purpose: retrieving public-domain, attributed commentary (Matthew Henry) on a biblical reference. It distinguishes itself from siblings by emphasizing 'never generated' and 'found and cited', though it lacks an explicit verb like 'get' or 'retrieve'.
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?
Usage is implied: this tool is for authoritative, attributed commentary rather than generated content. However, there is no explicit mention of when to use it versus alternatives or any exclusions, so guidance is minimal.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Several tools are near-duplicates: read_passage and resolve both fetch WEB text for a reference; word_study already includes every occurrence that word_occurrences returns; coach_next and coach_recommend both answer 'what's next.' Search/locate/cards_browse also overlap as discovery entry points, making tool selection ambiguous despite detailed descriptions.
Most names follow an object_verb snake_case pattern (cards_browse, study_create, seal_fetch), but there are many bare verbs/nouns (ask, audit, resolve, verify, canon, harmony) and inconsistent singular/plural pairs (card_get vs cards_browse, group_create vs groups_list, want_open vs wants_list). No camelCase, but the convention is not uniform.
86 tools is an extreme count for any single MCP server, far beyond the 3-15 well-scoped range; even a broad platform would be hard for an agent to navigate. Many tools belong to unrelated subdomains (coach, steward, mesh, calendar), making the surface unwieldy.
The want/offer flow has no accept/close tool, so an agent can open a want and offer a source but never see it resolved. Group and calendar coverage are one-directional (create/join only; no leave/delete/list/update), and there is no badge listing or way to update a study group. Core reading/verification/shelf flows are solid, but lifecycle gaps remain.