content-hash-cache-pattern

content-hash-cache-pattern is a skill for Claude Code, Codex from gongyijie85/dsh-ecc. It costs 51 tokens per session (1,306 once invoked), scanned A, a copy of content-hash-cache-pattern, MIT.

A file-processing cache that saves results under a SHA-256 fingerprint of the file contents. SHA-256 is a standard way to create a near-unique text identifier from data, so the cache does not depend on the file path.

In plain words
What is it for?
Use it for repeated PDF parsing, text extraction, or image analysis. It also covers adding cache and no-cache command-line options while keeping caching separate from existing processing functions.
Why use it?
It avoids repeating expensive work on unchanged files and automatically stops using an old result when the contents change. Renaming or moving a file does not invalidate a valid cached result.

Skill for Claude CodeCodex

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

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 skills/gongyijie85/dsh-ecc/content-hash-cache-pattern
Any agent
npx skills add gongyijie85/dsh-ecc --skill content-hash-cache-pattern
Clone the repo
git clone --depth 1 https://github.com/gongyijie85/dsh-ecc

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
[![agentmods](https://agentmods.dev/badge/skills/gongyijie85/dsh-ecc/content-hash-cache-pattern.svg)](https://agentmods.dev/skills/gongyijie85/dsh-ecc/content-hash-cache-pattern)
Your own site
<a href="https://agentmods.dev/skills/gongyijie85/dsh-ecc/content-hash-cache-pattern"><img src="https://agentmods.dev/badge/skills/gongyijie85/dsh-ecc/content-hash-cache-pattern.svg" alt="Measured on agentmods" height="20"></a>
Per session 51 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,306 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 94% 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 $0.00051 $0.01306
Opus 5 $0.00026 $0.00653
Sonnet 5 $0.00010 $0.00261
Haiku 4.5 $0.00005 $0.00131

Measured 6d ago against content hash c0242ee2fcb5, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, 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 6d 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

94% identical to content-hash-cache-pattern — 7 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.

skills/content-hash-cache-pattern/SKILL.md · 163 lines

How it starts

The opening of the file, as written. The whole thing — 163 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 · 163 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. 6d ago First seen · 163 lines · 51 tokens per session scan A c0242ee2fcb5

Subscribe to this mod's changes

content-hash-cache-pattern is a skill published in the GitHub repository gongyijie85/dsh-ecc (6 stars, last pushed 2d ago), licensed MIT. It adds 51 tokens to every session and 1,306 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 94% identical to content-hash-cache-pattern, differing in 7 lines, and is treated as a copy.

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