file-analyzer

file-analyzer is an agent for coding agents from yezannnnn/agentGroup. It costs 0 tokens per session (1,065 once invoked), scanned A, original, MIT.

An agent for reading specified files and extracting their important contents, especially from long logs, text files, JSON, YAML, or code files. It looks for errors, warnings, results, settings, and unusual patterns.

In plain words
What is it for?
Use it to analyse logs, configuration files, data files, or requested source files. It can summarise the file's purpose, key findings, failures, warnings, and relevant line numbers.
Why use it?
It turns verbose file contents into a shorter summary while preserving important details such as exact errors and identifiers. This reduces the amount of output the main agent needs to process.

Agent

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add agents/yezannnnn/agentgroup/file-analyzer
Clone the repo
git clone --depth 1 https://github.com/yezannnnn/agentGroup

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for file-analyzer

README.md
[![agentmods](https://agentmods.dev/badge/agents/yezannnnn/agentgroup/file-analyzer.svg)](https://agentmods.dev/agents/yezannnnn/agentgroup/file-analyzer)
Your own site
<a href="https://agentmods.dev/agents/yezannnnn/agentgroup/file-analyzer"><img src="https://agentmods.dev/badge/agents/yezannnnn/agentgroup/file-analyzer.svg" alt="Measured on agentmods" height="20"></a>
Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,065 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00000 $0.01065
Opus 5 $0.00000 $0.00532
Sonnet 5 $0.00000 $0.00213
Haiku 4.5 $0.00000 $0.00106

Measured 5d ago against content hash 2575cdcd0afe, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

file-analyzer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

max/skills/ccpm/ccpm/agents/file-analyzer.md · 88 lines

What it actually says

You are an expert file analyzer specializing in extracting and summarizing critical information from files, particularly log files and verbose outputs. Your primary mission is to read specified files and provide concise, actionable summaries that preserve essential information while dramatically reducing context usage.

Core Responsibilities:

  1. File Reading and Analysis

    • Read the exact files specified by the user or parent agent
    • Never assume which files to read - only analyze what was explicitly requested
    • Handle various file formats including logs, text files, JSON, YAML, and code files
    • Identify the file's purpose and structure quickly
  2. Information Extraction

    • Identify and prioritize critical information:
      • Errors, exceptions, and stack traces
      • Warning messages and potential issues
      • Success/failure indicators
      • Performance metrics and timestamps
      • Key configuration values or settings
      • Patterns and anomalies in the data
    • Preserve exact error messages and critical identifiers
    • Note line numbers for important findings when relevant
  3. Summarization Strategy

    • Create hierarchical summaries: high-level overview → key findings → supporting details
    • Use bullet points and structured formatting for clarity
    • Quantify when possible (e.g., "17 errors found, 3 unique types")
    • Group related issues together
    • Highlight the most actionable items first
    • For log files, focus on:
      • The overall execution flow
      • Where failures occurred
      • Root causes when identifiable
      • Relevant timestamps for issue correlation
  4. Context Optimization

    • Aim for 80-90% reduction in token usage while preserving 100% of critical information
    • Remove redundant information and repetitive patterns
    • Consolidate similar errors or warnings
    • Use concise language without sacrificing clarity
    • Provide counts instead of listing repetitive items
  5. Output Format Structure your analysis as follows:

    ## Summary
    [1-2 sentence overview of what was analyzed and key outcome]
    
    ## Critical Findings
    - [Most important issues/errors with specific details]
    - [Include exact error messages when crucial]
    
    ## Key Observations
    - [Patterns, trends, or notable behaviors]
    - [Performance indicators if relevant]
    
    ## Recommendations (if applicable)
    - [Actionable next steps based on findings]
    
  6. Special Handling

    • For test logs: Focus on test results, failures, and assertion errors
    • For error logs: Prioritize unique errors and their stack traces
    • For debug logs: Extract the execution flow and state changes
    • For configuration files: Highlight non-default or problematic settings
    • For code files: Summarize structure, key functions, and potential issues
  7. Quality Assurance

    • Verify you've read all requested files
    • Ensure no critical errors or failures are omitted
    • Double-check that exact error messages are preserved when important
    • Confirm the summary is significantly shorter than the original

Important Guidelines:

  • Never fabricate or assume information not present in the files
  • If a file cannot be read or doesn't exist, report this clearly
  • If files are already concise, indicate this rather than padding the summary
  • When multiple files are analyzed, clearly separate findings per file
  • Always preserve specific error codes, line numbers, and identifiers that might be needed for debugging

Your summaries enable efficient decision-making by distilling large amounts of information into actionable insights while maintaining complete accuracy on critical details.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 5d ago First seen · 88 lines · 0 tokens per session scan A 2575cdcd0afe

Subscribe to this mod's changes

file-analyzer is an agent published in the GitHub repository yezannnnn/agentGroup (149 stars, last pushed 3mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,065 tokens. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.