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.
/plugin marketplace add SteveGJones/ai-first-sdlc-practices/plugin install sdlc-knowledge-baseWrote 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.
[](https://agentmods.dev/skills/stevegjones/ai-first-sdlc-practices/kb-lint)<a href="https://agentmods.dev/skills/stevegjones/ai-first-sdlc-practices/kb-lint"><img src="https://agentmods.dev/badge/skills/stevegjones/ai-first-sdlc-practices/kb-lint/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.
<a href="https://agentmods.dev/skills/stevegjones/ai-first-sdlc-practices/kb-lint"><img src="https://agentmods.dev/badge/skills/stevegjones/ai-first-sdlc-practices/kb-lint.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00064 | $0.03400 |
| Opus 5.5 | $0.00026 | $0.01360 |
| Sonnet 5.5 | $0.00013 | $0.00680 |
| Haiku 4.5 | $0.00006 | $0.00340 |
Grade A, and why
kb-lint 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 1mo 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.
How it starts
The opening of the file, as written. The whole thing — 355 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Knowledge Base Lint
Periodic health-check for the project's knowledge base. This is the lint operation in the three-operations model (ingest / query / lint), adopted from Karpathy's LLM Wiki gist.
The staleness check that runs in environment validation catches one kind of drift (file changed since last index). Lint catches the other kinds: logical drift, orphan accumulation, missing concepts, contradictions, gaps. Both are needed.
Arguments
Optional --scope <pattern> to limit lint to a subset of library files. Default is the entire library.
Optional --strict-layer to fail with a non-zero exit when any library file has a missing or invalid layer: frontmatter field. Without this flag, layer violations are reported as warnings only in the Layer Compliance section.
Optional --strict-confidence to fail with a non-zero exit when any library file has a missing or invalid confidence: field. Without this flag, confidence violations are reported as warnings in the Layer Compliance section.
Optional --auto-fix to run the mechanical frontmatter fixer (kb_lint_fix.py) before lint. Auto-fix adds missing layer:, confidence:, and cross_references: fields with safe defaults, and creates stub frontmatter (with confidence: low, status: draft) for files that have no frontmatter at all. After fixing, the shelf-index is rebuilt before lint proceeds.
Examples:
--scope dora-*.md— lint only DORA-related files--scope library/architecture/*.md— lint a sub-directory--strict-layer— enforce layer compliance (used by this repo's CI)--strict-layer --scope *.md— combine both--strict-confidence— enforce confidence compliance--auto-fix --strict-layer --strict-confidence— fix mechanics, then enforce both- (no argument) — lint everything, warnings only
Preflight
- Verify the knowledge base is configured.
- Verify the shelf-index is fresh: invoke
kb-rebuild-indexesfirst if any library files are newer than the index. (The lint output is only meaningful against an up-to-date index.) - Verify there are at least 3 library files. Linting an empty or near-empty library is not useful.
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.
- 1mo ago First seen · 355 lines · 64 tokens per session scan A 8ea91976c09b
kb-lint is a skill published in the GitHub repository SteveGJones/ai-first-sdlc-practices (41 stars, last pushed 15d ago), licensed MIT. It adds 64 tokens to every session and 3,400 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-09-03.
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