content-hash-cache-pattern

content-hash-cache-pattern is a skill for Claude Code, Codex from ufy2024/AuC. It costs 30 tokens per session (1,384 once invoked), scanned A, a copy of content-hash-cache-pattern, MIT.

A caching pattern that stores expensive file-processing results under a SHA-256 fingerprint of the file's contents.

In plain words
What is it for?
Use it in pipelines that parse PDFs, extract text, or analyze images, with optional cache control in a command-line interface.
Why use it?
It avoids repeating work for unchanged files and still detects changes when files are moved, renamed, or edited.

Skill for Claude CodeCodex

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

Good fit Use it in pipelines that parse PDFs, extract text, or analyze images, with optional cache control in a command-line interface.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/ufy2024/auc/content-hash-cache-pattern
View source ↗ ufy2024/AuC
About the project

AuC is a Python framework for running a single AI agent with an asynchronous, pluggable reasoning loop, language-model adapters, permission levels, and observable events. It is used to build coding and conversational agents with tools, security checks, web interfaces, background jobs, evaluations, and isolated execution. The catalogue entries are skills for extending its agent workflow.

ufy2024/AuC · 1,090 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 ufy2024/AuC --skill content-hash-cache-pattern
Clone the repo
git clone --depth 1 https://github.com/ufy2024/AuC

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 content-hash-cache-pattern

README.md
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Your own site
<a href="https://agentmods.dev/skills/ufy2024/auc/content-hash-cache-pattern"><img src="https://agentmods.dev/badge/skills/ufy2024/auc/content-hash-cache-pattern/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for content-hash-cache-pattern

Your own site · 80×15
<a href="https://agentmods.dev/skills/ufy2024/auc/content-hash-cache-pattern"><img src="https://agentmods.dev/badge/skills/ufy2024/auc/content-hash-cache-pattern.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 30 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,384 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.
Origin 92% copy Near-identical to another mod 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 $0.00030 $0.01384
Opus 5 $0.00015 $0.00692
Sonnet 5 $0.00006 $0.00277
Haiku 4.5 $0.00003 $0.00138

Measured 8d ago against content hash 748e83c185c0, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

content-hash-cache-pattern 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 8d 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

This is a copy

92% identical to content-hash-cache-pattern — 28 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

auc/skill_library/bundled/content-hash-cache-pattern/SKILL.md · 182 lines

How it starts

The opening of the file, as written. The whole thing — 182 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Content-Hash File Cache Pattern

Cache expensive file processing results (PDF parsing, text extraction, image analysis) using SHA-256 content hashes as cache keys. Unlike path-based caching, this approach survives file moves/renames and auto-invalidates when content changes.

When to Activate

  • Building file processing pipelines (PDF, images, text extraction)
  • Processing cost is high and same files are processed repeatedly
  • Need a --cache/--no-cache CLI option
  • Want to add caching to existing pure functions without modifying them

Core Pattern

1. Content-Hash Based Cache Key

Use file content (not path) as the cache key:

import hashlib
from pathlib import Path

_HASH_CHUNK_SIZE = 65536  # 64KB chunks for large files

def compute_file_hash(path: Path) -> str:
    """SHA-256 of file contents (chunked for large files)."""
    if not path.is_file():
        raise FileNotFoundError(f"File not found: {path}")
    sha256 = hashlib.sha256()
    with open(path, "rb") as f:
        while True:
            chunk = f.read(_HASH_CHUNK_SIZE)
            if not chunk:
                break
            sha256.update(chunk)
    return sha256.hexdigest()

Why content hash? File rename/move = cache hit. Content change = automatic invalidation. No index file needed.

2. Frozen Dataclass for Cache Entry

from dataclasses import dataclass

@dataclass(frozen=True, slots=True)
class CacheEntry:
    file_hash: str
    source_path: str
    document: ExtractedDocument  # The cached result

3. File-Based Cache Storage

Each cache entry is stored as {hash}.json — O(1) lookup by hash, no index file required.

import json
from typing import Any

def write_cache(cache_dir: Path, entry: CacheEntry) -> None:
    cache_dir.mkdir(parents=True, exist_ok=True)
    cache_file = cache_dir / f"{entry.file_hash}.json"
    data = serialize_entry(entry)
    cache_file.write_text(json.dumps(data, ensure_ascii=False), encoding="utf-8")

def read_cache(cache_dir: Path, file_hash: str) -> CacheEntry | None:
    cache_file = cache_dir / f"{file_hash}.json"
    if not cache_file.is_file():
        return None
    try:
        raw = cache_file.read_text(encoding="utf-8")
        data = json.loads(raw)
        return deserialize_entry(data)
    except (json.JSONDecodeError, ValueError, KeyError):
        return None  # Treat corruption as cache miss

Read the full file on GitHub · 182 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. 8d ago First seen · 182 lines · 30 tokens per session scan A 748e83c185c0

Subscribe to this mod's changes

content-hash-cache-pattern is a skill published in the GitHub repository ufy2024/AuC (1,090 stars, last pushed 1mo ago), licensed MIT. It adds 30 tokens to every session and 1,384 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 92% identical to content-hash-cache-pattern, differing in 28 lines, and is treated as a copy.

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