tass: Instructions file for Codex

AGENTS.md

tass AGENTS.md is an instructions file for Codex, OpenCode from SIM-DAD/tass. It costs 1,174 tokens per session, scanned A, original, Apache-2.0.

Instructions for operating and extending TASS, an AI-oriented text-analysis system. They explain its agent interfaces, including MCP, a standard way for AI tools to communicate with applications, and its command-line interface.

In plain words
What is it for?
Use them to connect an AI agent to TASS, analyse text or transcript files, ingest chat logs, inspect matching words, and trace scores back to source documents.
Why use it?
They help an agent use TASS consistently while preserving its validation and provenance records. They also show which operations are available for analysing text, files, transcripts, and word usage.

Instructions file for CodexOpenCode

Written for Codex and OpenCode: the file is AGENTS.md. Also seen: mentions AGENTS.md.

This is SIM-DAD/tass's own configuration. It tells Codex and OpenCode how to work on tass itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything tass configures →

View source ↗ SIM-DAD/tass
Reuse

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.

Copy the file
curl -O https://raw.githubusercontent.com/SIM-DAD/tass/main/AGENTS.md
Clone the repo
git clone --depth 1 https://github.com/SIM-DAD/tass

Made for: Codex, OpenCode.

Wrote this? Show the measurements

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Per session 1,174 This file is loaded in full into every session.
When invoked 1,174 The same file — it is already loaded in full.
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 $0.01174 $0.01174
Opus 5.5 $0.00470 $0.00470
Sonnet 5.5 $0.00235 $0.00235
Haiku 4.5 $0.00117 $0.00117

Measured 2mo ago against content hash d74704743fb0, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

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.

AGENTS.md · 68 lines

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: 0 ok, 1 usage error, 2 runtime failure. Diagnostics go to stderr; stdout carries only data.

Contracts you can rely on (and must preserve)

  1. 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.
  2. Manifests are the provenance record. Every score writes <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.
  3. Licensing wall. Bundled = commercial-ok only. NRC/LIWC/GI and other restricted resources are user-imported (tass import-nrc, tass import-dic), flagged academic-only, and must NEVER be committed, bundled, or redistributed.
  4. Interpretation limits. Plain vader columns are lexicon-only (mean token valence). With --vader-rules / vader_rules: true you 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-column n_ coverage in group summaries. politeness v1 is a lexical + phrase approximation of the Danescu-Niculescu-Mizil taxonomy (no dependency parsing, position-blind), labeled as such. socialsent is the 2000s-decade frequent-words lexicon (Hamilton et al. 2016).
  5. For mean-metric columns, blank/null means "no hits" — never coerce it to 0.

Read the full file on GitHub · 68 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. 2mo ago First seen · 68 lines · 1,174 tokens per session scan A d74704743fb0

Subscribe to this mod's changes

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.

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