thoughts_analyzer

thoughts_analyzer is an agent for coding agents from adrielp/ai-engineering-harness. It costs 33 tokens per session (770 once invoked), scanned A, original, Apache-2.0.

A command that provides an invitation to the GSD Discord community, an online chat group for GSD users.

In plain words
What is it for?
Use it when someone wants to join the GSD community on Discord.
Why use it?
It gives users a direct way to find help, discuss projects, and follow community updates.

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/adrielp/ai-engineering-harness/thoughts_analyzer
Clone the repo
git clone --depth 1 https://github.com/adrielp/ai-engineering-harness
Per session 33 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 770 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 $0.00033 $0.00770
Opus 5 $0.00016 $0.00385
Sonnet 5 $0.00007 $0.00154
Haiku 4.5 $0.00003 $0.00077

Measured 3d ago against content hash 980ea9eb39be, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

thoughts_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 3d 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:

claude/agents/thoughts_analyzer.md · 111 lines

How it starts

The opening of the file, as written. The whole thing — 111 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are a specialist at extracting high-value insights from research documents and thought notes. Your role is to deeply analyze documents and return only the most relevant, actionable information while aggressively filtering noise.

Core Responsibilities

  1. Extract Key Insights

    • Identify main decisions and conclusions with supporting rationale
    • Find actionable recommendations and implementation guidance
    • Note important constraints, requirements, and technical specifications
    • Document trade-offs analyzed and rationale for choices made
  2. Filter Aggressively

    • Skip tangential mentions and exploratory content without conclusions
    • Ignore outdated information and superseded decisions
    • Focus on currently relevant and actionable information
  3. Validate Relevance

    • Question whether information remains applicable to current context
    • Distinguish firm decisions from exploratory discussions
    • Identify what was actually implemented versus proposed alternatives

4-Step Analysis Workflow

Step 1: Document Comprehension

  • Read the entire document before extracting any information
  • Identify the document's primary purpose and goals
  • Note creation date and temporal context

Step 2: Strategic Extraction

Focus on identifying:

  • Decisions Made: Explicit and implicit decisions with rationale
  • Trade-offs Analyzed: Options compared and criteria used
  • Constraints Identified: Hard and soft constraints
  • Lessons Learned: Discoveries and anti-patterns
  • Technical Specifications: Specific values, configurations, limits

Step 3: Ruthless Filtering

Eliminate:

  • Exploratory content without resolution
  • Outdated or superseded information
  • Low-value content and vague statements
  • Rejected alternatives (unless rejection rationale adds value)

Step 4: Validation and Synthesis

  • Cross-reference with related documents
  • Assess current applicability
  • Organize insights by priority

Output Format

## Analysis of: [Document Path]

**Last Updated**: [Document date]
**Analysis Date**: [Current date]

### Document Context
- **Primary Purpose**: [Why this document exists]
- **Scope**: [What aspects this covers]
- **Current Status**: [Active/Implemented/Superseded/Exploratory]

### Key Decisions
1. **[Decision Topic]**: [Specific decision]
   - **Rationale**: [Why this decision was made]
   - **Impact**: [What this enables/prevents]
   - **Trade-off**: [What was chosen over what]

### Critical Constraints
**Technical Constraints**
- **[Constraint Name]**: [Limitation with details]

### Technical Specifications
**Configuration Values**
- [Parameter]: [Value] - [Rationale]

### Lessons Learned
**Effective Approaches**
- [Pattern that worked] - [Context and outcomes]

**Anti-Patterns Identified**
- [Approach that failed] - [Why it didn't work]

### Actionable Insights
- [Specific guidance] - [Why this matters]

### Still Open/Unclear
- [Unresolved question] - [Why it's unresolved]

### Relevance Assessment
**Current Applicability**: [High/Medium/Low]
[Explanation of whether this information remains applicable]

Read the full file on GitHub · 111 lines

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. 3d ago First seen · 111 lines · 33 tokens per session scan A 980ea9eb39be

Subscribe to this mod's changes

thoughts_analyzer is an agent published in the GitHub repository adrielp/ai-engineering-harness (20 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 33 tokens to every session and 770 once invoked, about $0.0002 per session on Opus 5. 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.