Impri

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Server Quality Checklist

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Latest release: v0.1.0
Disambiguation5/5
Each tool has a clearly distinct purpose: watcher creation (two variants), listing, action pushing, decision awaiting, result reporting, and inbox status. No overlapping functionality.
Naming Consistency5/5
All tools use the 'impri_' prefix and follow a consistent verb_noun or verb_noun_noun pattern (e.g., create_watcher, push_action, list_watcher_presets). The naming is predictable and uniform.
Tool Count5/5
With 8 tools, the server covers two main domains—watcher management and action approval—without being bloated or sparse. Each tool serves a necessary role in the workflow.
Completeness4/5
The action lifecycle is well-covered (push, await, report, inbox status). For watchers, creation and listing are present, but missing update/delete operations are minor gaps that agents can work around.
Average 4.4/5 across 8 of 8 tools scored. Lowest: 3.8/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 226 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It discloses return values and suggests impact of backlog. However, it lacks details on scope (e.g., whose inbox) and does not explicitly state it is read-only or mention auth/rate limits. Adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no fluff. First sentence states purpose, second gives usage advice. Every part is relevant and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, so description should fully explain return values. It mentions pending count and titles but does not specify format (e.g., numeric, list of strings). For a simple tool, acceptable but could be more precise.
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?
No parameters exist, so baseline is 4. Description adds context about output and usage beyond the empty schema, meeting expectations.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool checks how many actions are waiting for human decisions and returns count and titles. It is a specific verb+resource but does not explicitly distinguish from sibling tools, though the purpose is distinct.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit when to use: 'Call this before starting a large batch of tasks' and advises on handling backlog. Does not mention alternatives or when not to use, but gives clear context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses the inbox effect and status options, which is adequate for a simple reporting tool. However, no annotations exist, so the description carries the full burden. It does not mention idempotency, error handling for invalid action_id, or any side effects beyond the inbox update.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise: two short paragraphs with clear front-loading of purpose. Every sentence adds value, no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and no nested objects, the description explains the tool's role in the audit loop lifecycle. It covers the statuses and when to call. Minor gap: does not specify if the report can be called multiple times, but overall sufficient for a simple result-reporting tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. Description adds minimal value beyond schema: restates enum values and clarifies detail usage for error vs success. Does not provide formatting or constraints beyond 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?
Clearly states the tool reports execution outcome of an approved action. Distinguishes from siblings like impri_push_action (which submits action) and impri_await_decision (which waits for decision) by targeting the post-approval reporting step.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly instructs to call after attempting an approved action, even on failure. Provides context of closing the audit loop and operator visibility. Lacks explicit alternatives or when-not-to-use, but sufficiently narrows usage to post-approval reporting.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It describes the output structure (count and summary line with id, name, kind, status) and optional filtering. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with purpose. Every sentence adds value without fluff.
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?
For a simple list tool with one optional parameter and no output schema, the description covers purpose, usage guidelines, and output structure completely.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the schema already describes the 'status' parameter with enum and description. The description reinforces filtering but adds no new semantic detail 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 verb 'List' and the resource 'configured watchers', with optional status filtering. It distinguishes from sibling tools like impri_create_watcher and impri_list_watcher_presets.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicit usage scenarios are provided: 'audit what is being monitored, check for degraded watchers, or find a watcher_id'. No exclusions or alternatives are mentioned, but the context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, description covers action lifecycle (submission, pending, approval/rejection, expiry), return values, and editable fields. Good detail on behavior beyond creation.
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?
Well-structured with intro, return value, and example. Efficient but could be slightly shorter; no wasted sentences.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For an 8-parameter submission tool without output schema, description covers key aspects: return shape, idempotency, expiry, preview format, and editable fields. Adequate for agent to invoke 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?
Schema has 100% coverage, description adds value by explaining workflow, providing example mapping, clarifying editable dot-notation, and noting idempotency. Does not repeat schema but enriches context.
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?
Clear verb 'Submit an action' and specific resource 'Impri human-approval inbox'. Differentiates from sibling impri_await_decision by noting polling, and example shows concrete usage.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly describes use case for human approval, mentions polling for decision, and provides example. Lacks explicit 'when not to use' instructions but context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses key behaviors: first run establishes baseline (no alerts), deduplication by URL/content-hash, delivery to inbox/webhook, and return object. Without annotations, this is a good level of transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is concise and well-structured: purpose, details, then example. Every sentence adds value with no redundancy or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers creation, scheduling, deduplication, first-run behavior, and return value. Lacks error handling or permission requirements, but overall complete for a create tool given no output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema only describes 'spec' as a backup reference to SPEC.md. The description adds a detailed example with all fields (name, kind, config, keywords, etc.), significantly enhancing understanding 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?
Description clearly states the verb 'Create' and resource 'watcher', and distinguishes from sibling tools like 'impri_list_watchers' and 'impri_create_watcher_from_preset'. The example and return value further clarify the purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Description explains when to use this tool (monitor external sources) and provides details on scheduling and deduplication. It does not explicitly mention when not to use it or alternatives, but the sibling tools imply a differentiation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fully discloses behavior: schedule/naming defaults, SSRF validation, config construction by presets, and return structure. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured: summary, details, then four diverse examples. Every sentence adds value, no fluff.
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?
For 4 params with nested objects and no output schema, description covers return fields, defaults, and parameter behavior comprehensively with examples.
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 coverage is 100% (baseline 3). Description adds meaning by explaining param type (key/value map of strings), requirement rules, and schedule override semantics.
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?
Clearly states it creates a watcher from a preset template, specifies what presets handle (URL building, keyword setup, SSRF validation), and differentiates from siblings like impri_create_watcher and impri_list_watcher_presets.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explains when to use the tool (have a preset ID and params) and references impri_list_watcher_presets for param definitions, but lacks explicit when-not-to-use or direct mention of alternative tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, but description explains what a preset is and provides an example output. It implies a safe read operation without side effects. The behavioral context is adequate for a simple listing tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is concise (4 sentences plus a helpful example). Every sentence adds value; no fluff.
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?
Tool is simple with no parameters and no output schema. Description fully explains purpose, presets structure, workflow, and related tool. Complete for this complexity level.
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?
No parameters in input schema (coverage 100%). Description does not need to add parameter information. Baseline score of 4 for zero parameters.
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 verb 'list' and the resource 'watcher presets'. It distinguishes itself from the sibling tool 'impri_create_watcher_from_preset' by indicating it is a prerequisite step.
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?
Explicitly says 'Call this first to discover which preset fits your monitoring goal, then use impri_create_watcher_from_preset'. Provides clear when-to-use and alternative.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It discloses polling interval (5 seconds), decision meanings (approved, rejected, expired), timeout behavior (stays pending), and suggests follow-up calls. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured: summary first, then details on polling, decisions, timeout, and typical usage. Every sentence adds value, no redundancy, and front-loaded.
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 complexity (polling, multiple outcomes, workflow integration) and no output schema, the description is complete. Covers what, when, how to interpret, and what to do on timeout.
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 coverage is 100% (baseline 3). Description adds meaning: action_id is 'returned by impri_push_action' and timeout_s explains default (300s) and behavior after timeout. This goes 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 states 'Poll until the human approves, rejects, or the timeout elapses.' The verb 'poll' and resource 'human decision' are specific. It distinguishes from siblings like impri_push_action (push action) and impri_inbox_status (queue depth).
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?
Provides a 'Typical usage' sequence (push → await → execute/report) and alternatives on timeout (impri_inbox_status). Clearly tells when to use and when not to (after push, before execution).
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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