Interpretable Context Methodology is a way to build agent workflows from numbered folders and Markdown files, with each file providing the prompts and context for one stage. It is for sequential tasks where a single AI agent follows a filesystem-defined process and people may review each stage. The catalogue skills support workflows built with this approach.
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 RinDig/Interpretable-Context-Methodology --skill elevenlabs-narrationgit clone --depth 1 https://github.com/RinDig/Interpretable-Context-MethodologyWrote 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/rindig/interpretable-context-methodology/elevenlabs-narration)<a href="https://agentmods.dev/skills/rindig/interpretable-context-methodology/elevenlabs-narration"><img src="https://agentmods.dev/badge/skills/rindig/interpretable-context-methodology/elevenlabs-narration.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00046 | $0.00623 |
| Opus 5 | $0.00023 | $0.00311 |
| Sonnet 5 | $0.00009 | $0.00125 |
| Haiku 4.5 | $0.00005 | $0.00062 |
Grade A, and why
elevenlabs-narration 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 8d 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 — 53 lines — stays where its author put it; the contents beside it link to each section on GitHub.
When to Use
Use this skill in Stage 03 (voice). It takes a finished script (Stage 02 output) and produces an mp3.
What You Need Before Calling
- A
.envfile withELEVEN_API_KEYandELEVEN_VOICE_IDpopulated locally. See../../shared/env-template.md. - Python with
elevenlabsandpython-dotenvinstalled. - A script file in the workspace that contains a
## ► PASTE THIS into ElevenLabsheading followed by two---rules. The narration sits between those rules.
The skill never writes the API key or voice id into a committed file. Credentials stay in .env.
How It Works
- Read the script file.
- Find the
PASTE THIS into ElevenLabsheading. The case-insensitive match handles►,▶, or>prefixes. - Extract everything between the next two
---rules. Strip any lines starting with>(markdown blockquote callouts to the human). - Load
.envviapython-dotenv. - Call
client.text_to_speech.convert(text=..., voice_id=..., model_id=..., output_format=..., voice_settings=VoiceSettings(...)). - Save the returned audio to
audio/{videoN}.mp3(master). - Copy that file to
remotion/public/audio/{videoN}.mp3(runtime, sostaticFile()finds it).
The reference implementation is in scripts/generate-audio.py. Copy it into the project root and adjust the SCRIPTS mapping for your file layout.
Voice Settings
This workspace is configured for:
- Voice label:
{{ELEVEN_VOICE_LABEL}}(the real id lives in.env) - Model:
{{ELEVEN_MODEL_ID}} - Stability:
{{ELEVEN_STABILITY}} - Similarity boost:
{{ELEVEN_SIMILARITY_BOOST}} - Speed:
{{ELEVEN_SPEED}} - Output:
{{ELEVEN_OUTPUT_FORMAT}}
Override any of these by setting the matching ELEVEN_* variable in .env before the call.
Rules
rules/paste-block.md-- exact format the script must use so extraction worksrules/tone-tags.md--[brackets]tags ElevenLabs honors and the ones it does not
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 8d ago First seen · 53 lines · 46 tokens per session scan A 3c2079154041
elevenlabs-narration is a skill published in the GitHub repository RinDig/Interpretable-Context-Methodology (1,151 stars, last pushed 1mo ago), licensed MIT. It adds 46 tokens to every session and 623 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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