Borrowing it
Nothing to install: this file belongs to SIM-DAD/tass. 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/SIM-DAD/tass/main/AGENTS.mdgit clone --depth 1 https://github.com/SIM-DAD/tassWrote 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/instructions/sim-dad/tass/agents-md)<a href="https://agentmods.dev/instructions/sim-dad/tass/agents-md"><img src="https://agentmods.dev/badge/instructions/sim-dad/tass/agents-md/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/instructions/sim-dad/tass/agents-md"><img src="https://agentmods.dev/badge/instructions/sim-dad/tass/agents-md.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 | $0.01174 | $0.01174 |
| Opus 5.5 | $0.00470 | $0.00470 |
| Sonnet 5.5 | $0.00235 | $0.00235 |
| Haiku 4.5 | $0.00117 | $0.00117 |
Grade A, and why
tass AGENTS.md 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 — 68 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md — driving TASS as an AI agent
TASS is designed to be operated by AI. Two equivalent surfaces exist; both run the exact same code paths, validation, and provenance machinery.
Surface 1: MCP (preferred for agents)
tass mcp serves stdio JSON-RPC (register once: claude mcp add --scope user tass -- tass mcp).
Tools:
| Tool | Use it to |
|---|---|
tass_dicts |
Learn the bundled lexicons + their category ids, licenses, citations. Call first. |
tass_analyze_text |
Score a string directly; returns tokens, per-category hits/weighted/percent/mean + matched forms. Pass vader_rules: true for the rules-based sentiment block. |
tass_score_file |
Batch-score a CSV/TXT corpus to files: scored CSV, group summaries, windowed trajectories, JSON rows, citations — plus the run manifest. |
tass_ingest |
Turn speaker-labeled transcripts ([M:SS] **SPEAKER:** …) — or chat logs ([stamp] <user> … / [stamp] user: …) with format: "chat" — into the turn-level CSV tass_score_file expects. |
tass_exemplars |
Trace any score back to the highest/lowest-scoring documents and the exact words that fired. |
tass_kwic |
Concordance lines for a word or stem* across a corpus. |
All file paths must be absolute. File-writing tools return a log naming every artifact written; read the files yourself afterwards if you need their contents.
Surface 2: CLI (for shells and scripts)
tass help is the authoritative usage text. Machine-friendly modes:
tass dicts --json— the bundle as JSON.tass analyze --text "…" | --stdin | -i file.txt [--lexicons a,b] [--all]— JSON to stdout.tass score … --json rows.json— typed row objects alongside the CSV.- Exit codes:
0ok,1usage error,2runtime failure. Diagnostics go to stderr; stdout carries only data.
Contracts you can rely on (and must preserve)
- Determinism. Same inputs ⇒ byte-identical outputs. Do not add timestamps, random ids, or environment-dependent values to any output. Verify nontrivial changes by running a score twice and hashing.
- Manifests are the provenance record. Every
scorewrites<output>.manifest.json(input SHA-256s, lexicon license/class/citation, settings,academicOnlyUsed). When you report results to a human, cite from the manifest — never from memory. - Licensing wall. Bundled =
commercial-okonly. NRC/LIWC/GI and other restricted resources are user-imported (tass import-nrc,tass import-dic), flaggedacademic-only, and must NEVER be committed, bundled, or redistributed. - Interpretation limits. Plain
vadercolumns are lexicon-only (mean token valence). With--vader-rules/vader_rules: trueyou additionally get the TASS implementation of the published VADER heuristics (negation, boosters, ALL-CAPS, punctuation, but-clauses, emoticons, idiom tables) — report those as "TASS VADER-rules compound", never as the canonical "VADER compound" (tokenizer corner cases and emoji handling differ). NoRaRe norm lexicons (warriner-vad, concreteness, aoa) are Concepticon-mapped subsets — check per-columnn_coverage in group summaries.politenessv1 is a lexical + phrase approximation of the Danescu-Niculescu-Mizil taxonomy (no dependency parsing, position-blind), labeled as such.socialsentis the 2000s-decade frequent-words lexicon (Hamilton et al. 2016). - For
mean-metric columns, blank/null means "no hits" — never coerce it to 0.
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 · 68 lines · 1,174 tokens per session scan A d74704743fb0
tass AGENTS.md is an instructions file published in the GitHub repository SIM-DAD/tass (0 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 1,174 tokens to every session, about $0.0047 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.
tass AGENTS.md compared with instructions from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| tass AGENTS.mdSIM-DAD/tass | Instructions file | 0 | 3mo ago | Apache-2.0 | A | 1,174 | Codex, OpenCode |
| vscode buildNext.instructions.mdmicrosoft/vscode | Instructions file | 195k | today | MIT | A | 9,719 | GitHub Copilot |
| vscode oss-third-party-notices.instructions.mdmicrosoft/vscode | Instructions file | 195k | today | MIT | A | 5,516 | GitHub Copilot |
| next.js AGENTS.mdvercel/next.js | Instructions file | 143k | yesterday | MIT | A | 7,461 | Codex, OpenCode |
| langchain AGENTS.mdlangchain-ai/langchain | Instructions file | 149k | today | MIT | A | 4,680 | Codex, OpenCode |
| vscode copilot-instructions.mdmicrosoft/vscode | Instructions file | 195k | today | MIT | A | 3,093 | GitHub Copilot |
| vscode model-prompts.instructions.mdmicrosoft/vscode | Instructions file | 195k | today | MIT | A | 2,022 | GitHub Copilot |