PineForge-Codegen

Server Quality Checklist

Profile completionA complete profile improves this server's visibility in search results.

Latest release: v0.9.27
Disambiguation5/5
Each tool has a distinct purpose: backtesting single vs. grid, data fetching, symbol listing, engine management, transpilation. No overlap in functionality.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern in snake_case (e.g., backtest_pine, fetch_binance_ohlcv), making them predictable and easy to understand.
Tool Count5/5
8 tools cover the core workflow of PineScript backtesting (transpile, run, sweep, fetch data, manage engine) without redundancy or missing essentials.
Completeness4/5
The set covers transpilation, single backtest, parameter sweeps, data fetching, symbol validation, and engine updates. Minor gaps like multi-exchange support or visualization exist but do not hinder the primary use case.
Average 4.5/5 across 8 of 8 tools scored. Lowest: 3.9/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 45 commits in the last 12 weeks
- Last stable release on August 13, 2026
- 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.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
This repository includes a glama.json configuration file.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
View related servers

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

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 are provided, so the description carries full burden. It discloses that the tool runs docker pull, which is a network operation that may be slow and requires Docker installed. However, it does not mention potential failures (e.g., network issues, authentication), side effects (modifying local Docker images), or prerequisites.
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 with no wasted words. The first sentence clearly states the action, and the second provides usage context. Excellent front-loading and conciseness.
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?
For a simple tool with one optional parameter and no output schema, the description is adequate but lacks context about prerequisites (e.g., Docker installation), return value or outcome after pull, and error handling. Given the sibling tool check_engine_image, more detail on postconditions would help.
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% for the single parameter. The description adds meaning by stating the default value and noting the image is the runtime image, but the schema already has a description. Baseline 3 is appropriate.
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?
The description clearly states the action ('run docker pull') and the specific resource ('pineforge-release runtime image'). It also mentions the context (on user's machine) and hints at sibling differentiation by noting usefulness before backtest_pine, though it does not explicitly distinguish from check_engine_image.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides implied usage: 'Useful before the first backtest_pine call.' However, it does not specify when not to use this tool (e.g., if image already exists) or mention alternatives like check_engine_image. No explicit exclusions or comparative guidance.
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?
Describes internal process (transpile once, re-run compiled strategy), output format (ranked list, best), and performance constraints (max_combinations, concurrency overhead). Lacks explicit statement on destructiveness or side effects, but overall clear.
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 paragraph, front-loaded with usage guidance, efficient sentences. Could be slightly more concise but appropriate for complexity.
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?
Covers all key aspects: when to use, process, output, constraints, concurrency, and schema included. No output schema, but description sufficiently explains return structure.
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 provides 100% coverage for all 13 parameters. Description adds general context (e.g., default max_combinations, concurrency advice) but does not significantly deepen meaning beyond what schema already offers.
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 'optimize, sweep, tune, compare' and resource 'PineScript parameter values'. Explicitly distinguishes from sibling 'backtest_pine' by stating when to use each.
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 explicit when-to-use ('optimize, sweep, tune, or compare') and when-not-to-use ('for one fixed configuration use backtest_pine'). Also gives context on concurrency and max_combinations.
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 burden. It discloses no network, local execution, returns text as C++. No hidden behavioral traits omitted.
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 wasted words. All information is front-loaded and essential.
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?
Low complexity with 2 params, no output schema. Description covers return type and primary use case. Could mention Docker requirement, but still adequate.
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 100%, description adds value by specifying source must include '//@version=6' and explaining image default. Adds meaning 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?
Description clearly states verb 'transpile', resource 'PineScript v6 source to C++', and distinguishes from sibling 'backtest_pine'.
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 says 'use backtest_pine if you also want to run the strategy', providing clear context for when to use this tool. Could mention Docker dependency but overall strong.
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?
Since no annotations are provided, the description carries full burden. It fully discloses that the backtest is local, uses Docker, requires an OHLCV CSV with specific format, and explains optional parameters like inputs and overrides. It also details large report offloading and return format.
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 well-structured with the main purpose front-loaded and separate paragraphs for different aspects. While it is fairly long, every sentence contributes meaningful information, so it remains efficient.
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 the tool's complexity (7 parameters, nested objects, no output schema), the description adequately covers the return format, large report handling, and links to sibling tools. It could briefly mention what happens if no trades or errors, but overall it is complete.
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 description coverage is 100%, so baseline is 3. The main description adds some additional context (e.g., why to prefer this tool, explanation of overrides vs. runtime, env var usage), but does not substantially enhance understanding beyond the schema descriptions themselves.
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 starts with a specific verb and resource ('Run a real, deterministic backtest of a PineScript v6 strategy') and clearly distinguishes itself from the sibling tool backtest_pine_grid, which is for sweeps. The purpose is unmistakable.
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 explicit guidance on when to use: 'prefer this over estimating...', lists example user requests, and directly states 'Use backtest_pine_grid for sweeps' to advise against misuse. This gives clear context for tool selection.
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; description fills gap by stating results are cached 5 min and free. It does not disclose rate limits or auth needs, but for a read-only tool this is sufficient. 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 and filters. Every word earns its place, 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?
No output schema, but description covers purpose, filters, caching, and cost. For a listing tool, this is complete enough. Could mention return format but not essential.
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 coverage is 100%, and description adds examples (e.g., 'USDT', 'BTC', 'TRADING', 'PERPETUAL') and explains query as substring. This goes beyond the schema, providing clear 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?
The description clearly states the tool lists/validates symbols for OHLCV fetching, distinguishing it from sibling tools like fetch_binance_ohlcv. It specifies the resource (symbols) and action (list/validate) with context.
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?
The description implies usage for selecting symbols before fetching OHLCV data, with filters provided. It doesn't explicitly exclude alternatives, but the context with sibling tools makes it apparent. Could add when-not-to-use.
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 discloses the tool returns full detail and lists, error marker for unknown IDs, and states 'Local, free, no engine run' indicating low cost and non-destructive nature. Does not detail exact return structure but sufficient for agent to understand behavior.
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?
Three concise sentences with front-loaded purpose, no redundant words. Each sentence adds essential information: what it returns, when to use, and error behavior.
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?
Fully adequate for a simple one-parameter tool with full schema coverage. Covers return content, usage examples, error handling, and cost characteristics. No output schema needed given clarity of description.
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 already describes the 'topic' parameter (100% coverage). Description adds value by listing example IDs and source (list_coverage_topics), and explains error behavior for unknown topics, providing beyond-schema context for parameter usage.
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 tool returns detailed supported/unsupported feature lists for one coverage topic ID, using specific verb 'Returns' and resource 'coverage topic detail'. It distinguishes from sibling list_coverage_topics by emphasizing it retrieves details for a single topic.
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 guidance: 'Use when you are about to work in a feature area and need to know precisely which functions there are implemented vs skipped' with concrete examples (request.security, ta.*). Also describes error behavior for unknown IDs. No explicit when-not-to-use, 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?
No annotations provided, so description carries full burden. Clearly states it is read-only ('Does not run the engine'), which is the key behavioral trait. No additional disclosure needed for a 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?
Single paragraph is well-structured, front-loaded with purpose, and contains all necessary details without extraneous information.
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 no output schema, description fully specifies return structure: two groups with keys, types, enum?, description. Complete for a discovery tool with no 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?
Tool has 0 parameters; schema coverage 100%. Description adds value by explaining the structure of the returned catalog, which compensates for lack of params. Baseline for 0 params is 4.
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 it returns a catalog of engine knobs for backtest_pine/backtest_pine_grid and explicitly says 'Does not run the engine', distinguishing it from sibling tools that execute backtests.
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?
The description explicitly advises using this tool before issuing a backtest to discover knobs. It doesn't explicitly state when not to use it, but the context of sibling tools makes the usage clear.
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 carries full burden and does well: it explains the mechanism (docker manifest inspect, no layers downloaded), the return values (up_to_date, recommend_pull), the auto_pull behavior, and notes version independence from the MCP server.
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?
The description is concise (5 sentences) with no fluff. Each sentence adds unique information, starting with the core purpose, then mechanism, returns, options, and an important caveat. Well structured and front-loaded.
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, the description returns what it provides ('up_to_date + recommend_pull') but lacks details on the format or error handling. It covers the main behavior well but is not fully detailed.
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% with descriptions, but the tool description adds default values for both parameters and clarifies auto_pull behavior beyond the schema, enhancing understanding.
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 'check' and the specific resource 'pineforge-release Docker image', distinguishing it from sibling tools like 'pull_engine_image'. It says exactly what the tool does: checks if the local image is up to date.
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?
The description implies the tool is for checking rather than pulling, and the auto_pull option allows pulling when needed. However, it does not explicitly mention the sibling 'pull_engine_image' as an alternative for pure pulling, leaving some ambiguity.
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 behavioral traits: pagination for >1000 bars, output path restrictions (cwd unless env var set), and exact CSV format, including timestamp interpretation.
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?
The description is concise (~150 words) and front-loaded with the core purpose. Each sentence adds value, covering format, pagination, path constraint, and market-specific interval support without redundancy.
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 the 7 parameters (3 required), schema coverage, and no output schema, the description provides complete context: it specifies the CSV output format, pagination, path constraints, and interval restrictions, making the tool self-contained.
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?
The schema has 100% coverage, and the description adds extra context beyond schema descriptions, such as defaults for limit/start_time/end_time, interval restrictions per market, and the hint to use 'binance_symbols' for symbol validation.
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 specifies the verb 'Fetch' and the resource 'OHLCV candles from Binance public API', and details the output format and market types. It distinguishes itself from siblings like 'binance_symbols' by focusing on data retrieval rather than symbol validation.
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?
The description implicitly guides usage by stating it fetches data for backtesting and suggests using 'binance_symbols' for symbol validation. It does not explicitly list alternatives or when-not-to-use, but the context is clear enough for the agent.
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 provided, the description fully carries the burden. It discloses the resolution logic (exact match, then longest namespace prefix, then alias), the possible statuses and their meanings, and that the tool is local, free, and requires no engine run.
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 a single paragraph but efficiently conveys purpose, usage, behavior, and return structure. Every sentence adds value, though it could be slightly more structured. No redundancy.
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 one parameter, no output schema, and no annotations, the description provides all necessary context: purpose, usage cases, behavioral details, and the return fields. It fully equips an agent to select and invoke the tool correctly.
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?
The schema covers the single parameter 'feature' with a clear description, but the tool description adds valuable context with examples and explains the resolution algorithm. This enhances understanding beyond the schema alone.
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 tool answers whether PineForge supports a given Pine v6 identifier or namespace, with explicit examples. It distinguishes itself from sibling tools like transpile_pine and backtest_pine by focusing on feature support checking.
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 explicit guidance on when to use: before relying on uncertain functions while writing strategies, and for diagnosing backtest issues. It also explains the behavior of visual/alert APIs being parsed-and-skipped, which informs when not to rely on them.
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: output includes one-line status, summary, legend, and coverage version; statuses are defined (supported/partial/unsupported/via_transpiler); and it notes the tool is 'Cheap, free, local — no engine run, no I/O.' No contradictions exist.
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?
The description is front-loaded with the most critical instruction ('START HERE') and packs detailed information (status legend, behavior, sibling references) into a compact, well-structured paragraph. Every sentence adds value without redundancy.
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 no parameters, no output schema, and no annotations, the description thoroughly explains what the tool does, what it returns (list with status and summary), the meaning of each status, and why it should be used first. It covers all necessary context for correct invocation.
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?
The input schema has zero parameters, so the description need not add parameter meaning. The baseline for zero parameters is 4. The description does not introduce any ambiguity about 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 states the tool lists coverage topics for Pine v6 strategies on PineForge, and explicitly distinguishes it from sibling tools get_coverage_topic and check_pine_feature. It uses the specific verb 'list' and clarifies the resource (coverage topics) and scope (Pine v6 subset).
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?
The description explicitly says 'START HERE before writing, porting, or backtesting a Pine v6 strategy on PineForge' and advises checking coverage first to avoid silent misbehavior. It also names alternatives for deeper drilling: 'drill in with get_coverage_topic' and 'check_pine_feature to look up a single identifier.'
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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