Skip to main content
Glama

validate_strategy_no_lookahead

Detects lookahead bias in backtest strategy code by statically analyzing the AST for common patterns like forward-indexing and future-dated attributes. Run to identify potential bugs before trusting backtest results.

Instructions

Static-analysis check for the most common backtest bug: lookahead bias. Walks the strategy code's AST and flags negative .shift(N), forward-index arithmetic like df.iloc[i+1], open-upper slices inside per-bar callbacks, and attribute names that look future-dated (next_*, future_*, lookahead_*). Heuristic, not a proof — false negatives are possible. Run before trusting any backtest result.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
codeYesPython source of the strategy module / class.
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations exist, so the description carries full burden. It discloses heuristic nature, false negatives, and specific patterns checked (AST walk, negative shift, forward-index, attribute names). However, it lacks mention of the return format or side effects (presumably read-only).

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?

Four sentences, no fluff, front-loaded with purpose. Every sentence adds value: purpose, method, patterns, limitations. Highly efficient.

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?

Given single parameter and no output schema, the description lacks a hint about what the tool returns (e.g., warnings list, success indicator). Also does not clarify whether it is state-modifying (should not be). Otherwise, it covers when to use and limitations.

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 a basic description of 'code' parameter. The description adds significant context by explaining what kind of code (strategy module/class) and what patterns are analyzed, enriching the schema's minimal description.

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 is a static-analysis check for lookahead bias, a specific bug. It uses a specific verb ('checks') and resource ('strategy code's AST'), and its name distinguishes it from the broader validate_strategy sibling.

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 provides clear usage context: 'Run before trusting any backtest result.' It does not explicitly exclude scenarios or mention alternatives, but the context is strong enough for an agent to decide when to invoke it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/FLOX-Foundation/flox'

If you have feedback or need assistance with the MCP directory API, please join our Discord server