AllocContext
Server Quality Checklist
Latest release: v0.3.0
- Disambiguation4/5
Tools have distinct purposes: checking drift, retrieving context, comparing deltas, market data, portfolio state, and rebalancing plans. The overlapping between check_allocation_band(s) and get_rebalance_plan is minor as one is for drift checking and the other for generating moves.
Naming Consistency5/5All tool names follow a consistent verb_noun pattern in snake_case (check_, get_), making the API predictable and easy to navigate.
Tool Count5/5With 8 tools covering portfolio context, drift checking, market data, and rebalancing, the count is well-scoped for the domain. Each tool serves a clear purpose without redundancy.
Completeness4/5The tool set covers core portfolio monitoring and planning (drift, context, deltas, rebalance plan). Missing execution tools to actually rebalance, but that may be intentional. Minor gap in updating targets or bands, but those are passed as parameters.
Average 3.6/5 across 8 of 8 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 160 commits in the last 12 weeks
- Last stable release on
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
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
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description bears full burden. It explains the behavior of as_of and match parameters, but omits behaviors for scope, assets, target_pct, and band. It does not state whether this is read-only or any side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two sentences. The first sentence states the main purpose, and the second explains two key parameters. No unnecessary words, but could be more structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 6 parameters and an output schema, the description only covers 2 parameters and does not differentiate from 7 sibling tools. It lacks guidance on how to use the other parameters or when to pick this tool over others.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%. The description adds meaning for as_of (ISO timestamp) and match (at_or_before logic), but the other 4 parameters (scope, assets, target_pct, band) are not described at all, leaving their semantics unclear.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it loads a saved ContextBundle snapshot from ingest history, specifying the action and resource. However, it does not distinguish from sibling tools like get_context_bundle, which might retrieve the current context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for historical snapshots with ISO timestamp and matching logic, but lacks explicit when-not-to-use or comparison with alternatives. It provides context but no exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description bears full burden. It describes the check and hint output but omits side effects, permissions, or error behavior, leaving behavioral traits unclear.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief with two sentences, front-loading the main purpose and parameters. It is efficient and avoids redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool complexity (required nested objects, output schema exists), the description covers core logic and hint types but lacks details on error handling, input validation, or full output specification.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 0% description coverage, so the description must compensate. It labels allocation_pct and target_pct as asset-specific (BTC/ETH/CASH) and band as the drift threshold, but doesn't detail the object structure or value formats.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool checks allocation band weights against a target and returns a hint. It specifies the assets (BTC/ETH/CASH) and output types, but does not distinguish from the similar sibling 'check_allocation_bands'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions all three inputs are required (though band has a default) and gives a usage hint for bundle drift. However, it lacks explicit when-to-use or alternative guidance compared to sibling tools.
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?
No annotations are provided, so the description carries the full burden. It discloses that live ingest requires API keys and that cached uses a local DB, but it does not mention if the tool is read-only, rate limits, or potential side effects. The behavioral aspects are partially covered.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long, front-loading the purpose in the first sentence and parameter specifics in the second. No redundant words; every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has three parameters and an output schema (though not shown). The description provides enough to understand the data sources and freshness options but does not detail the output format or how it integrates with sibling tools. Given the output schema exists, return values are covered, but more context on when to use this tool in a workflow would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It explains the assets parameter (default, optional) and the freshness parameter (values and semantics). However, the scope parameter is only given a default value without any explanation of its meaning or allowed values.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description lists specific components (sentiment, macro events, FRED indicators, ETF flows, market breadth) that clearly define the tool's scope. It distinguishes from sibling tools like check_allocation_band which likely focus on different data. However, it lacks an explicit action verb (e.g., 'retrieves') and the phrase 'Fused market backdrop' is somewhat vague.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains the optional assets filter and the two freshness modes (cached vs live) with their prerequisites. It does not specify when to use this tool over alternatives like get_context_at or other siblings, nor does it provide exclusions or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden for behavioral disclosure. It only states the basic operation without detailing side effects, safety (e.g., read-only), or edge cases (e.g., behavior if prior_as_of is after current). This is insufficient for an agent to safely invoke the tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with no redundant information. It efficiently conveys the core purpose and a key usage note, earning its place without fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With an output schema present, the return values are documented elsewhere. However, the tool compares snapshots and the description lacks details on comparison semantics, error conditions, or the nature of 'notable_shifts.' While minimally viable, it could be more complete given the tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It clarifies that prior_as_of is required and current_as_of can be omitted for the latest bundle. However, it does not explain 'scope' (default 'daily') or 'assets' (list of strings), leaving the agent to guess their purpose and valid values.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Compare two ContextBundle snapshots and return notable_shifts.' This is a specific verb (Compare) and resource (ContextBundle snapshots), and it distinguishes itself from siblings like get_context_at (which retrieves a single snapshot) and get_context_bundle (which fetches a bundle).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides guidance on required vs optional parameters: 'prior_as_of is required; omit current_as_of for latest live bundle.' This helps the agent understand how to use the tool, though it does not explicitly mention when not to use it or compare with alternatives.
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, so description carries full burden. It explains caching vs live behavior, optional allocation analysis, and delta comparison. No contradictions; adds meaningful context beyond schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, front-loaded with core purpose, then optional features, then freshness behavior. No waste; every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 5 parameters (none required) and an output schema, the description covers core output, options, and behavior. Lacks error/limitation notes but is sufficient for this complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but description explains assets (default BTC, ETH), target_pct/band for allocation analysis, and freshness modes. Missing explanation of 'scope' parameter, but overall adds significant meaning.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
Description states it returns a full ContextBundle JSON with holdings, market, sentiment, macro, regime hints, and delta. It distinguishes from siblings by mentioning optional allocation analysis, but does not explicitly contrast with tools like get_context_at or get_context_delta.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Implies usage by describing features (assets filter, allocation analysis, freshness modes) but provides no explicit when-to-use or when-not-to-use guidance relative to sibling tools.
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?
No annotations provided, so description carries full burden. It explains the tool's output (deltas, move lines) and the effect of optional parameters (band returns a band_check block). It does not disclose side effects, auth requirements, rate limits, or whether the operation is read-only. The existence of an output schema partially compensates, but the description could be more explicit.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Description is two sentences: first states the primary function, second details parameters and options. Information is front-loaded, no redundant phrases, and every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 5 parameters (including nested objects), an output schema, and a planning context, the description covers the main output and parameter effects. However, it does not explain the expected keys in allocation_pct and target_pct objects, nor the structure of the move lines output. The presence of an output schema mitigates this, but for an agent to invoke correctly, more detail on object parameters would be beneficial.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so description must compensate. It explains the purpose of required params (allocation_pct, target_pct, nav_usd) and optional params (band adds band_check, exchange adjusts wording). The description does not detail the structure of the object parameters (e.g., keys in allocation_pct), but the mention of BTC/ETH/CASH split provides meaningful context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool produces 'USD deltas and exchange-style move lines to reach a target BTC/ETH/CASH split'. It identifies the specific resource (rebalance plan) and action (get). The mention of splitting into BTC/ETH/CASH distinguishes it from sibling tools like check_allocation_band which focus on band checking.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Description lists required parameters (allocation_pct, target_pct, nav_usd) and optional ones (band, exchange), implying when to include them. However, it does not provide explicit guidance on when to choose this tool over alternatives like check_allocation_bands, leaving the agent to infer usage context.
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 provided, the description carries the full burden. It explicitly states 'read-only' (implying no state changes) and 'Credentials are never stored,' which are valuable behavioral disclosures. However, it omits details about error handling, rate limits, or data freshness guarantees beyond 'Live'.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise at three sentences, with the most important information front-loaded: what the tool returns. It adds optional behavior and security notes efficiently, with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the output schema exists, the description does not need to detail return formats. It adequately mentions NAV, holdings, band weights, and optional allocation_analysis. It notes 'Live' data and supported exchanges, but could be more complete by clarifying how holdings are structured and that the tool is read-only.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must explain all parameters. It covers exchange, api_key, and api_secret implicitly through 'read-only exchange credentials' and explicitly mentions target_pct ('attaches allocation_analysis'). However, the 'band' parameter is not described, leaving a gap in understanding its purpose.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns 'Live portfolio NAV, holdings[], and band weights' using 'read-only exchange credentials', which distinguishes it from sibling tools like check_allocation_band that focus on allocations. It specifies supported exchanges, making the purpose precise.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description lacks explicit guidance on when to use this tool versus alternatives. It does not mention prerequisites or exclusion criteria. While it notes the optional target_pct parameter attaches allocation_analysis, it does not clarify when to prefer this over sibling allocation-checking tools.
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?
No annotations are provided, so the description must cover behavioral traits. It mentions evaluation and default band but does not disclose side effects (e.g., read-only), error handling, or prerequisites. Adequate but incomplete.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences: first states purpose, second details parameters. No unnecessary words, front-loaded with key action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Has output schema, so describing returns is unnecessary. But the description lacks details about the allocation_pct parameter (asset mapping) and does not set expectations for result interpretation. Passable but not thorough.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so description must add meaning. It clarifies that scenarios is an array of objects with required target_pct and optional name/band. However, allocation_pct structure (a map of asset to percentage) is not explained, leaving some ambiguity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool evaluates allocation drift across multiple scenarios, with a specific verb and resource. It distinguishes from the singular 'check_allocation_band' sibling by emphasizing batch evaluation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Description explains that each scenario requires target_pct and optionally name/band, with a default. It implies use for multiple scenarios but does not explicitly contrast with alternatives like get_rebalance_plan or check_allocation_band.
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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