Borrowing it
Nothing to install: this file belongs to mickeytony0215-png/obsidian-llm-wiki. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/mickeytony0215-png/obsidian-llm-wiki/main/.claude/commands/lint-related-work.mdgit clone --depth 1 https://github.com/mickeytony0215-png/obsidian-llm-wikiWrote 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/commands/mickeytony0215-png/obsidian-llm-wiki/lint-related-work)<a href="https://agentmods.dev/commands/mickeytony0215-png/obsidian-llm-wiki/lint-related-work"><img src="https://agentmods.dev/badge/commands/mickeytony0215-png/obsidian-llm-wiki/lint-related-work/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/commands/mickeytony0215-png/obsidian-llm-wiki/lint-related-work"><img src="https://agentmods.dev/badge/commands/mickeytony0215-png/obsidian-llm-wiki/lint-related-work.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 | $0.00040 | $0.01474 |
| Opus 5 | $0.00020 | $0.00737 |
| Sonnet 5 | $0.00008 | $0.00295 |
| Haiku 4.5 | $0.00004 | $0.00147 |
Grade A, and why
lint-related-work 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 12d 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 — 150 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Automated fairness check for Related Work framing. Two phases: a fast mechanical pass and an optional cross-validation pass against baseline PDFs.
This repo ships the command spec only. The implementation is intentionally not bundled; fork users either reimplement the checks described below or wrap their preferred linter under this command name.
Use cases
- Reading a new paper:
$ARGUMENTSis a note or PDF path. Flag framing red flags immediately after/read-paper. - Writing your own paper:
$ARGUMENTSis your draft path. Self-check for unfair framing before submission. - Preparing a lab-seminar talk: lint the paper's main baselines before the talk.
Input format
/lint-related-work <path-to-note-or-pdf>
.mdnote: read the Related Work or Problem-statement section and check every baseline description..pdf: extract withpdftotext -layout, then locate the "Related Work" / "State of the Art" / "II." section.- No argument: scan the current note.
Checks
Phase 1: mechanical red flags (fast)
-
Absolutist-wording grep: search the Related Work and baseline-description text for:
- Completeness claims:
completely overlooked,entirely fails,cannot support,never,always fails - Exaggeration claims:
significant burden,excessive,severely limits,critically flawed
Output: line number, quoted text, risk grade.
- Completeness claims:
-
Baseline extraction: grep for
Author et al. [N]patterns and list every cited baseline. -
Scope keyword check (when input is a
.mdnote):- Pull the paper's own keywords from frontmatter
tagsor Index Terms. - For each baseline, if its topic clearly does not match (e.g. an authentication paper citing a task-scheduling paper as a baseline), flag it.
- Pull the paper's own keywords from frontmatter
Phase 2: cross-validation against the baseline PDF (slow, requires baseline in raw/papers/)
- Self-description check (needs baseline PDF):
- For any baseline criticised with absolutist wording in Phase 1, look for its PDF in
raw/papers/. - Extract the baseline's Abstract + Contributions sections.
- Grep the baseline for the criticised claim.
- Example: the paper criticises a baseline as "centralized", but the baseline's Abstract describes itself as "distributed" — severe inconsistency.
- For any baseline criticised with absolutist wording in Phase 1, look for its PDF in
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.
- 12d ago First seen · 150 lines · 40 tokens per session scan A 4f1844501e99
lint-related-work is a command published in the GitHub repository mickeytony0215-png/obsidian-llm-wiki (2 stars, last pushed 2mo ago), licensed MIT. It adds 40 tokens to every session and 1,474 once invoked, about $0.0002 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 2026-08-31.
Other commands, from other repositories
daily-okr
Run a daily knowledge compound loop (7 KR). Invoke with /daily-okr or "start my daily review".
session-learn
Extract knowledge from the current session. Invoke with /session-learn or "extract this session".
status
Show memex statistics and status including projects, memos, and pending items.
open
Open the memex vault in Finder or Obsidian.
okf
A command that exports a private knowledge wiki into an OKF-compatible bundle. OKF is a format for packaging knowledge, with a separate guarded mode for preparing material to share externally.
ingest
A command for adding information to a file-based knowledge wiki from web pages, files, or text notes. It classifies the material, updates or creates wiki pages, and adds links between related pages.