kb-ingest-batch

kb-ingest-batch is a skill for Claude Code from SteveGJones/ai-first-sdlc-practices. It costs 63 tokens per session (1,137 once invoked), scanned A, original, MIT.

A batch workflow for adding multiple staged Markdown files from a project's raw knowledge folder to its knowledge base. It records progress so completed and failed files can be handled separately later.

In plain words
What is it for?
Use it to ingest many raw Markdown sources, optionally process several at once, retry failed files, and track batch progress.
Why use it?
It removes the need to process every source manually and supports resuming an interrupted batch. It also consolidates the final index and activity log updates.

Skill for Claude Code

Written for Claude Code: disable-model-invocation in frontmatter. Also seen: mentions CLAUDE.md.

Runs only inside its plugin — its command needs a path that Claude Code sets for a plugin’s own hooks and for nothing else. Install the plugin, not this.

Part of the sdlc-knowledge-base plugin — 16 skills, 4 agents shipped together

Good fit Use it to ingest many raw Markdown sources, optionally process several at once, retry failed files, and track batch progress.

Compare 6 skills from other repositories ↓
Install

Getting it into your agent

This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.

Claude Code
/plugin marketplace add SteveGJones/ai-first-sdlc-practices
Claude Code
/plugin install sdlc-knowledge-base

Made for: Claude Code.

Or install sdlc-knowledge-base, the plugin that ships this one along with the rest of its 16 skills, 4 agents.

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 kb-ingest-batch

README.md
[![agentmods](https://agentmods.dev/badge/skills/stevegjones/ai-first-sdlc-practices/kb-ingest-batch/github.svg)](https://agentmods.dev/skills/stevegjones/ai-first-sdlc-practices/kb-ingest-batch)
Your own site
<a href="https://agentmods.dev/skills/stevegjones/ai-first-sdlc-practices/kb-ingest-batch"><img src="https://agentmods.dev/badge/skills/stevegjones/ai-first-sdlc-practices/kb-ingest-batch/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 kb-ingest-batch

Your own site · 80×15
<a href="https://agentmods.dev/skills/stevegjones/ai-first-sdlc-practices/kb-ingest-batch"><img src="https://agentmods.dev/badge/skills/stevegjones/ai-first-sdlc-practices/kb-ingest-batch.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 63 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,137 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 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 $0.00063 $0.01137
Opus 5 $0.00032 $0.00568
Sonnet 5 $0.00013 $0.00227
Haiku 4.5 $0.00006 $0.00114

Measured 11d ago against content hash 313e6daf9f2e, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

kb-ingest-batch 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 11d 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.

plugins/sdlc-knowledge-base/skills/kb-ingest-batch/SKILL.md · 122 lines

How it starts

The opening of the file, as written. The whole thing — 122 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Deprecated (v0.3.0+): Prefer /sdlc-knowledge-base:kb-ingest-bulk, which adds a parallel map-reduce path that can update existing shared files (this skill is create-only). kb-ingest-batch remains functional for simple create-only batches.

Batch Ingestion

Drive agent-knowledge-updater over every staged file in library/raw/, with progress tracking and resume support. Second stage of the batch workflow: prepare (kb-prepare-batch) then ingest (this skill).

Arguments

Argument Description
(none) Process all .md files in library/raw/ with status: raw
<dir> Process all .md files in this directory
--parallel <N> Dispatch up to N agents concurrently (max: 5)
--retry-failed Re-queue failed entries from a prior run

Resume behaviour

Progress is tracked in library/raw/.batch-progress.json. On re-invocation:

  • completed files are skipped
  • failed files are left alone unless --retry-failed is passed
  • New status: raw files in raw/ are appended to pending

Preflight

  1. Read CLAUDE.md to resolve library_path, shelf_index_path, log_path
  2. Verify agent-knowledge-updater agent is available

Steps

1. Discover files and build/update manifest

python3 -c "
import sys, os, importlib.util, json
PLUGIN_ROOT = os.environ.get('CLAUDE_PLUGIN_ROOT', '')
SCRIPTS = os.path.join(PLUGIN_ROOT, 'scripts')
INIT = os.path.join(SCRIPTS, '__init__.py')
if os.path.isfile(INIT) and 'sdlc_knowledge_base_scripts' not in sys.modules:
    spec = importlib.util.spec_from_file_location(
        'sdlc_knowledge_base_scripts', INIT, submodule_search_locations=[SCRIPTS])
    if spec and spec.loader:
        mod = importlib.util.module_from_spec(spec)
        sys.modules['sdlc_knowledge_base_scripts'] = mod
        spec.loader.exec_module(mod)
from sdlc_knowledge_base_scripts.kb_ingest_batch import (
    discover_raw_files, load_manifest, build_manifest, save_manifest, retry_failed
)
from pathlib import Path
raw_dir = Path('<raw_dir>')
manifest_path = raw_dir / '.batch-progress.json'
existing = load_manifest(manifest_path)
if existing and <retry_failed_flag>:
    existing = retry_failed(existing)
source_files = discover_raw_files(raw_dir)
manifest = build_manifest(source_files, existing=existing)
save_manifest(manifest_path, manifest)
print(json.dumps({'pending': len(manifest['pending']), 'total': manifest['total']}))
"

Read the full file on GitHub · 122 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. 11d ago First seen · 122 lines · 63 tokens per session scan A 313e6daf9f2e

Subscribe to this mod's changes

kb-ingest-batch is a skill published in the GitHub repository SteveGJones/ai-first-sdlc-practices (41 stars, last pushed 1mo ago), licensed MIT. It adds 63 tokens to every session and 1,137 once invoked, about $0.0003 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.

Related

Other skills, from other repositories

media-ingest

Ingest video, audio, PDF, book, screenshot, and GitHub repo content into the brain. Multi-format handling with entity extraction and backlink propagation. Covers video-ingest, youtube-ingest, and book-ingest subtypes.

garrytan/gbrain · 52 tokens

mem0-oss-to-platform

Plan and then execute a migration of a project from the mem0 open-source / self-hosted SDK (the local Memory class) to the mem0 Platform / hosted / managed SDK (the MemoryClient class). Use this whenever a developer wants to move, switch, or migrate their mem0 usage off OSS/self-hosted to the hosted API — e.g.…

mem0ai/mem0 · 273 tokens

Cortex

Operate Cortex, the LifeOS memory system — the typed Knowledge Archive (People, Companies, Ideas, Research with typed related: links) plus recall of prior work sessions, ISAs, and conversations. Search, add, harvest, develop, ingest, distill, graph-navigate, recall. USE WHEN cortex, knowledge, knowledge base, search…

danielmiessler/LifeOS · 196 tokens

memory

Use when the user asks to remember, recall, forget, update, search, or inspect durable OpenSquilla memory, including profile facts in USER.md and long-term notes in MEMORY.md or memory//.md.

opensquilla/opensquilla · 44 tokens

ha-data-stores

Map of Hope Agent's local data stores and safe read-only query workflow. Use when the user asks where Hope Agent stores data, wants to inspect sessions/messages/memory/logs/background jobs/knowledge indexes/settings, asks the model to query local app data, or debugging requires checking persisted state. Trigger…

shiwenwen/hope-agent · 115 tokens

shellm

Reference for the shellm system — recursive LLM shell, identity management, memory, skills, trajectory, and all CLI tools. Use when working on shellm itself, debugging agent behavior, or understanding how the pieces fit together.

laude-institute/headlong · 49 tokens