faf_get_tierResolve the FAF tier for a given numeric score. Returns the tier symbol (Trophy/Gold/Silver/Bronze/etc.) per the canonical tier-table.
| Name | Required | Description | Default |
|---|---|---|---|
| score | Yes | Numeric score 0-100. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Output schema / (root)Previous value: -{
- "properties": {
- "content": {
- "items": {
- "properties": {
- "text": {
- "description": "Human-readable tool result.",
- "type": "string"
- },
- "type": {
- "const": "text",
- "type": "string"
- }
- },
- "required": [
- "type",
- "text"
- ],
- "type": "object"
- },
- "type": "array"
- },
- "isError": {
- "description": "True when the tool failed.",
- "type": "boolean"
- }
- },
- "required": [
- "content",
- "isError"
- ],
- "type": "object"
-}New value: +nullOutput schema / (root)Previous value: -nullNew value: +{
+ "properties": {
+ "content": {
+ "items": {
+ "properties": {
+ "text": {
+ "description": "Human-readable tool result.",
+ "type": "string"
+ },
+ "type": {
+ "const": "text",
+ "type": "string"
+ }
+ },
+ "required": [
+ "type",
+ "text"
+ ],
+ "type": "object"
+ },
+ "type": "array"
+ },
+ "isError": {
+ "description": "True when the tool failed.",
+ "type": "boolean"
+ }
+ },
+ "required": [
+ "content",
+ "isError"
+ ],
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. Description adds the canonical tier-table context, clarifying determinism and shared reference. It doesn't enumerate all possible symbols ('etc.'), but it states the main ones and relies on a canonical table, which is sufficient.
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?
One short, front-loaded sentence capturing the purpose and return type; the tier symbol list is concise. No extraneous 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?
Complete enough: has one fully documented parameter, no output schema needed because return shape is described, and annotations cover safety. The only minor gap is the unspecified full symbol list (e.g., 'etc.'), but for a fixed table this is acceptable.
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 has 100% coverage for score (0-100). Description doesn't add range clarifications beyond this but aligns with the schema. It implies the score is numeric, but the schema description is adequate.
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?
Clear verb 'Resolve' with a specific resource ('FAF tier for a given numeric score') and describes the return value (tier symbol per canonical tier-table). No sibling overlap; indistinguishable from siblings like faf_analyze.
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 context signals (tier-table lookup) implicitly indicate it's for mapping a score to a tier, not for complex analysis. Doesn't state exclusions versus siblings, but it's a simple deterministic resolver, and sibling names don't compete directly for this task.
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 faf_* tools overlap: faf_score, faf_validate, faf_analyze, and faf_gate all grade or gate content, while faf_get_tier and gf_analyze both address tier determination. Search and discovery also fragment into faf_collections_search, search_context, search_bfy_tag, list_tags, and tag_intel, making it easy for an agent to pick a nearly-equivalent tool.
The set consistently uses snake_case and leans heavily on the faf_ domain prefix, but the style is not uniform: faf_score, faf_validate, and faf_estimate_tokens are action-based, while faf_memory, faf_section, and faf_gate are noun- or verb-like with less clear command intent. Overall still readable, but the pattern is mixed.
19 tools is at the upper end of a reasonable number for a context/analysis system, especially with faf_ prefix family. However, some tools could be consolidated; faf_analyze overlaps faf_score+validate+get_tier, the several gone by explicit domain; several search/ag tools overlap, and the broad read-only surface leaves no obvious fns for create/update/delete operations.
This is a heavy read/analysis and scoring surface, but it lacks obvious write/update/delete primitives for persistent context entities. There are soul list/get and search tools, a faf generator, scoring/validation tools, and recommendations, but no create_soul, update_soul, delete_soul, or analogous persistent mutation operations for .faf/.fafm data. For 'persistent project context,' the set feels read-only and incomplete.