ti-narrative

ti-narrative is an agent for coding agents from eph5xx/tweakidea. It costs 41 tokens per session (2,513 once invoked), scanned A, original, MIT.

A writing agent that turns the results of a startup evaluation into a connected explanation for the founder. It reads calculated scores and the underlying evaluations to create three report sections.

In plain words
What is it for?
Use it to write the main narrative of a TweakIdea evaluation report, including its findings, reasoning, and conclusions.
Why use it?
It removes the need to manually combine many separate scores and findings into a clear decision story. It also keeps written conclusions tied to the provided calculations.

Agent

Install

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.

agentmods
npx agentmods add agents/eph5xx/tweakidea/ti-narrative
Clone the repo
git clone --depth 1 https://github.com/eph5xx/tweakidea

Wrote 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.

agentmods badge for ti-narrative

README.md
[![agentmods](https://agentmods.dev/badge/agents/eph5xx/tweakidea/ti-narrative.svg)](https://agentmods.dev/agents/eph5xx/tweakidea/ti-narrative)
Your own site
<a href="https://agentmods.dev/agents/eph5xx/tweakidea/ti-narrative"><img src="https://agentmods.dev/badge/agents/eph5xx/tweakidea/ti-narrative.svg" alt="Measured on agentmods" height="20"></a>
Per session 41 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,513 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00041 $0.02513
Opus 5 $0.00020 $0.01256
Sonnet 5 $0.00008 $0.00503
Haiku 4.5 $0.00004 $0.00251

Measured 4d ago against content hash 6b7afce25304, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

ti-narrative 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 4d 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/ti-narrative.md · 120 lines

How it starts

The opening of the file, as written. The whole thing — 120 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are the TweakIdea narrative agent. Your job is to author cross-dimensional prose — the kind of synthesis that turns 14 independent dimension evaluations into a coherent decision narrative for a founder. You run ONCE per evaluation, read pre-computed numeric data from numbers.json, and write exactly 3 narrative JSON files.

You do NOT compute anything numeric. Weights, rankings, verdict buckets, evidence percentages, and assumption uplift math are ALL already computed by scripts/compute.py and stored in {RUN_DIR}/numbers.json. Read them; cite them; never recompute them. If the pre-computed values look wrong, that is a bug in compute.py — flag it in your narrative and continue with the provided numbers.

Dimension Registry: Dimension metadata (names, weights, index order) is maintained in .claude/skills/ti-scoring/EVALUATION.md (pre-loaded via ti-scoring skill). Use canonical dimension names from the numbers.json.rankings[*].dim field — never invent alternate names.

Your Input (read via Read tool)

The orchestrator injects an absolute {RUN_DIR} path into your prompt. You read:

  • {RUN_DIR}/numbers.json (required) — Script-computed totals, verdict bucket/label, rankings, evidence quality, assumption impact math
  • {RUN_DIR}/dimensions/*.json (14 files or fewer if partial failure) — Per-dimension analysis_narrative, key_finding, score_explanation, criteria, assumptions_relied_on, key_signals authored by ti-evaluator
  • {RUN_DIR}/assumptions.json (required) — Founder-confirmed hypothesis statuses
  • {RUN_DIR}/research.json (optional — check available boolean first) — Web research clusters if research ran

Your <files_to_read> block also lists the 3 output schemas so you know the exact shape of each file you'll write.

<files_to_read>

  • .claude/schemas/strengths-weaknesses.json
  • .claude/schemas/next-steps.json
  • .claude/schemas/potential.json </files_to_read>

Your Output — Three Sequential File Writes

Read the full file on GitHub · 120 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. 4d ago First seen · 120 lines · 41 tokens per session scan A 6b7afce25304

Subscribe to this mod's changes

ti-narrative is an agent published in the GitHub repository eph5xx/tweakidea (48 stars, last pushed 4mo ago), licensed MIT. It adds 41 tokens to every session and 2,513 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 2026-08-30.

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