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.
npx skills add nlebovits/parseltongue-claude --skill parseltonguegit clone --depth 1 https://github.com/nlebovits/parseltongue-claudeWrote 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/nlebovits/parseltongue-claude/parseltongue)<a href="https://agentmods.dev/skills/nlebovits/parseltongue-claude/parseltongue"><img src="https://agentmods.dev/badge/skills/nlebovits/parseltongue-claude/parseltongue/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/nlebovits/parseltongue-claude/parseltongue"><img src="https://agentmods.dev/badge/skills/nlebovits/parseltongue-claude/parseltongue.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 | $0.00062 | $0.01694 |
| Opus 5.5 | $0.00025 | $0.00678 |
| Sonnet 5.5 | $0.00012 | $0.00339 |
| Haiku 4.5 | $0.00006 | $0.00169 |
Grade A, and why
parseltongue 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 2mo 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 — 223 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Parseltongue Grounded Analysis
Analyze documents with provable claims. Every fact traces to a verbatim quote. Hallucinations are automatically detected.
Quick Start
/parseltongue [paste document] What are the key findings?
Or with a file:
/parseltongue @report.pdf Are there any red flags in this SEC filing?
How It Works
┌─────────────────────────────────────────────────────────────────────┐
│ 1. REGISTER │ Load document into Parseltongue session │
│ 2. EXTRACT │ Generate facts with verbatim :evidence quotes │
│ 3. DERIVE │ Draw conclusions using formal logic │
│ 4. VERIFY │ Check all quotes match source (catch hallucinations) │
│ 5. ANSWER │ Respond with [ref:symbol] citations │
└─────────────────────────────────────────────────────────────────────┘
Instructions
Step 1: Create Session & Register Document
mcp__parseltongue__parseltongue_create_session
session_id: "analysis-{timestamp}"
mcp__parseltongue__parseltongue_register_document
session_id: "analysis-..."
name: "doc" # or descriptive name like "10k-filing"
content: [document text]
Step 2: Extract Facts (Pass 1)
Generate Parseltongue DSL with facts. Every fact MUST have a verbatim quote.
(fact revenue-q3 42000000
:evidence (evidence "doc"
:quotes ("Total revenue for Q3 2024 was $42 million")
:explanation "Quarterly revenue figure"))
(fact growth-target 40000000
:evidence (evidence "doc"
:quotes ("Growth target was $40 million")
:explanation "Target figure for comparison"))
Rules:
:quotesmust be EXACT text from the document (case-insensitive matching allowed)- One fact per distinct claim
- Use descriptive symbol names (kebab-case)
Load and check:
mcp__parseltongue__parseltongue_load_dsl
session_id: "analysis-..."
dsl_source: [your DSL]
If unverified_count > 0, you hallucinated! Fix the quotes.
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.
- 2mo ago First seen · 223 lines · 62 tokens per session scan A fda71b1c8788
parseltongue is a skill published in the GitHub repository nlebovits/parseltongue-claude (0 stars, last pushed 7mo ago), licensed Apache-2.0. It adds 62 tokens to every session and 1,694 once invoked, about $0.0002 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 2026-08-31.
parseltongue compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| parseltonguenlebovits/parseltongue-claude | Skill | 0 | 7mo ago | Apache-2.0 | A | 62 | Claude Code, Codex |
| orbit-notionnexu-io/open-design | Skill | 107k | today | Apache-2.0 | A | 117 | Claude Code, Codex |
| instrument-data-to-allotropeanthropics/knowledge-work-plugins | Skill | 35k | yesterday | Apache-2.0 | A | 123 | Claude Code |
| apify-youtube-transcript-scrapersickn33/agentic-awesome-skills | Skill | 49k | yesterday | MIT | A | 48 | Claude Code |
| legal-holdanthropics/claude-for-legal | Skill | 9.9k | yesterday | Apache-2.0 | A | 68 | Claude Code |
| report-to-pdfasgeirtj/system_prompts_leaks | Skill | 71k | yesterday | CC0-1.0 | A | 17 | Claude Code, Codex |
| artifact-template-minimal-letterheadasgeirtj/system_prompts_leaks | Skill | 71k | yesterday | CC0-1.0 | A | 54 | Claude Code, Codex |