history-analysis

history-analysis is a skill for Claude Code, Codex from microsoft/AutoSaddler. It costs 27 tokens per session (1,652 once invoked), scanned A, original, MIT.

A method for reviewing the complete history of an agent-improvement project and extracting the lessons relevant to the current iteration. It organizes results from earlier iterations without discarding older or newer entries.

In plain words
What is it for?
Use it at the start of an iteration to summarize previous experiments, compare results, identify recurring patterns, and choose informed next steps.
Why use it?
Long histories are easy to misread when only the beginning or end is inspected. Reviewing the full evolution helps avoid repeating failed approaches and missing earlier findings.

Skill for Claude CodeCodex ✓ vendor

Written for no agent in particular: nothing here depends on one.

Good fit Use it at the start of an iteration to summarize previous experiments, compare results, identify recurring patterns, and choose informed next steps.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/microsoft/autosaddler/history-analysis
About the project

AutoSaddler is a system that improves LLM-agent harnesses by diagnosing execution traces and applying structured changes to prompts, tools, middleware, and agent-loop logic. It evaluates candidate updates for their ability to generalize beyond the traces that motivated them. The catalogue add-ons represent workflows for using AutoSaddler.

microsoft/AutoSaddler · 177 stars · on GitHub

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.

Any agent
npx skills add microsoft/AutoSaddler --skill history-analysis
Clone the repo
git clone --depth 1 https://github.com/microsoft/AutoSaddler

Made for: Claude Code, Codex.

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 history-analysis

README.md
[![agentmods](https://agentmods.dev/badge/skills/microsoft/autosaddler/history-analysis.svg)](https://agentmods.dev/skills/microsoft/autosaddler/history-analysis)
Your own site
<a href="https://agentmods.dev/skills/microsoft/autosaddler/history-analysis"><img src="https://agentmods.dev/badge/skills/microsoft/autosaddler/history-analysis.svg" alt="Measured on agentmods" height="20"></a>
Per session 27 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,652 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 1 finding, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • medium Output Handling · line 3
    Output size or generation rate is not bounded. Unbounded output enables denial-of-service through resource exhaustion, log flooding, or context-window stuffing.
    Fix: Set explicit limits on output length, generation count, and rate. Use max_tokens and truncation to prevent unbounded output.
How audits are shown
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 5.1 $0.00027 $0.01652
Opus 5 $0.00014 $0.00826
Sonnet 5 $0.00005 $0.00330
Haiku 4.5 $0.00003 $0.00165

Measured 7d ago against content hash ff5883e08b34, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

history-analysis 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 7d 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.

src/autosaddler/v1/proposer/autosaddler/skills/history-analysis/SKILL.md · 187 lines

How it starts

The opening of the file, as written. The whole thing — 187 lines — stays where its author put it; the contents beside it link to each section on GitHub.

History Analysis

Overview

As iterations accumulate, the output of evo-dag show history grows too large to read in a single terminal command. Naively piping through head -200 or tail -200 discards critical information — early iterations' lessons are lost with tail, and recent results are lost with head. This skill provides a structured methodology to analyze the complete history using targeted CLI commands, producing a focused summary of what matters for the current iteration.

When to Use

At the start of every session (Session 0, 1, and 2) before any other work. The history analysis provides the context needed for informed decisions — skipping it leads to repeated mistakes, redundant patches, and missed lessons.

The Problem with Truncation

Do NOT pipe evo-dag show history through head, tail, or any truncation command. This loses information:

  • head -N: Loses all recent iterations' results and reflections
  • tail -N: Loses early iterations' foundational lessons and patterns
  • Increasing the number (head -300, tail -500) is a losing battle — the history grows every iteration

History Analysis Procedure

Step 1: Quick Orientation

Start with small, complete outputs to establish context:

# DAG topology and best candidate (always small output)
evo-dag summary

# DAG lineage visualization (always small output)
evo-dag show lineage

From this, note:

  • How many iterations have been run
  • Which candidate has the best dev score
  • The current lineage path

Step 2: Full History via File Redirect

Redirect the full history to a temporary file and read it with file tools. This avoids terminal output truncation entirely:

evo-dag show history > /tmp/evo_history.txt

Then read the file in sections using file reading tools (e.g., cat with line ranges, or IDE file reading). This lets you see the complete history regardless of length.

Read the file in manageable sections:

  • Start from the beginning to understand early foundational changes
  • Read the end to see the most recent iterations
  • Search for specific patterns or scenario IDs as needed

Read the full file on GitHub · 187 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. 7d ago First seen · 187 lines · 27 tokens per session scan A ff5883e08b34

Subscribe to this mod's changes

history-analysis is a skill published in the GitHub repository microsoft/AutoSaddler (177 stars, last pushed 13d ago), licensed MIT. It adds 27 tokens to every session and 1,652 once invoked, about $0.0001 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.

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