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 toejough/engram --skill sensors-add-skillgit clone --depth 1 https://github.com/toejough/engramWrote 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/toejough/engram/sensors-add-skill)<a href="https://agentmods.dev/skills/toejough/engram/sensors-add-skill"><img src="https://agentmods.dev/badge/skills/toejough/engram/sensors-add-skill/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/toejough/engram/sensors-add-skill"><img src="https://agentmods.dev/badge/skills/toejough/engram/sensors-add-skill.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 | $0.00030 | $0.00304 |
| Opus 5.5 | $0.00012 | $0.00122 |
| Sonnet 5.5 | $0.00006 | $0.00061 |
| Haiku 4.5 | $0.00003 | $0.00030 |
Grade A, and why
sensors-add-skill 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 25d 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.
What it actually says
Add Sensor Type to Telemetry System
Register a new sensor type in the telemetry system following the project's established conventions.
Procedure
-
Add a new entry to lib/sensors/registry.txt in tab-separated format: <sensor_id>:\t<sensor_name>\t. Example line:
pressure_v2:1.0\tpressure\t2024-02-01 -
Run the codegen script to update type definitions:
python3 scripts/sensors.py -
Create a migration file in migrations/ with naming pattern NNNN_sensor_<sensor_id>.go where NNNN is the next 4-digit sequence number (the first migration is 0001; use the next 4-digit number after the highest existing one). Example: for sensor_id pressure_v2 with no prior migrations, create 0001_sensor_pressure_v2.go. The migration must contain a func init() block that calls registerSensor(<sensor_id>).
-
Add an entry to TELEMETRY_CHANGELOG.log with exact format:
[YYYY-MM-DD HH:MM:SS] <operator> Added sensor <id>:<version> -
Verify all changes are staged in git (do not commit yet).
-
Run
make validateto verify the sensor registration is complete and correct.
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.
- 25d ago First seen · 23 lines · 30 tokens per session scan A 848377a58be2
sensors-add-skill is a skill published in the GitHub repository toejough/engram (8 stars, last pushed yesterday), licensed Apache-2.0. It adds 30 tokens to every session and 304 once invoked, about $0.0001 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 2026-09-21.
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