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 Vortx-AI/emem --skill emem-field-tokensgit clone --depth 1 https://github.com/Vortx-AI/ememWrote 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/vortx-ai/emem/emem-field-tokens)<a href="https://agentmods.dev/skills/vortx-ai/emem/emem-field-tokens"><img src="https://agentmods.dev/badge/skills/vortx-ai/emem/emem-field-tokens/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/vortx-ai/emem/emem-field-tokens"><img src="https://agentmods.dev/badge/skills/vortx-ai/emem/emem-field-tokens.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 6 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Supply Chain · line 71 Remote code is downloaded and executed. This bypasses code review and could introduce malicious code.Fix: Avoid downloading and executing remote scripts. Use trusted packages from PyPI/npm. If remote fetch is required, verify checksums and use HTTPS.
- medium Data Exfiltration · line 57 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 84 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 102 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 112 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 129 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
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 | $0.00137 | $0.02493 |
| Opus 5.5 | $0.00055 | $0.00997 |
| Sonnet 5.5 | $0.00027 | $0.00499 |
| Haiku 4.5 | $0.00014 | $0.00249 |
Grade A, and why
emem-field-tokens scanned grade A with 1 finding 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 28d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -sf -X POST https://emem.dev/v1/band_raster \ How it starts
The opening of the file, as written. The whole thing — 172 lines — stays where its author put it; the contents beside it link to each section on GitHub.
emem-field-tokens
Network use. The commands in this skill send and receive JSON (and, where a step says so, an image or a raster file) to
https://emem.devonly, the service the plugin's MCP server connects to. Nothing they download is executed. The files underscripts/read local files and make no network calls.
A world model reads a field over an area across time, not a set of points. This skill fetches that field from emem as a signed artifact anyone can re-derive.
| Call | Returns |
|---|---|
POST /v1/band_raster |
one native-resolution field over a bbox at one time, plus an emem:raster: token |
POST /v1/band_composite |
a cloud-free median composite over a date window (s2_median_composite@1), same shape |
POST /v1/band_cube |
the same field over several dates: a signed manifest over raster slices, as an emem:cube: token |
POST /v1/raster_bundle |
several rasters as one set, as an emem:rasterset: token |
POST /v1/raster/resolve, /v1/cube/resolve, /v1/raster_bundle/resolve |
walk a token back to its record; {"spot_check": true} also re-hashes the pixels for you |
POST /v1/cells_in_bbox |
the cell64 addresses in a bbox, paged, when you want addresses rather than a grid |
The receipt does not attest a value. It attests a derivation: this
responder computed the artifact whose blake3 is artifact_cid, from a
pinned Sentinel-2 scene, over a content-addressed area (aoi_cid) and
time. Re-fetch the bytes and re-hash them, or re-run the recipe from the
pinned scene, and you get the same artifact.
When to invoke
- "Give me the 10 m red-band grid over this farm, not per-cell scalars."
- "Build a time series of near-infrared over this AOI across the summer."
- "I need pixels over this area that a stranger can re-derive."
For one value at one place use
emem-locate-and-recall. For
per-cell facts inside an area use
emem-recall-polygon. For a picture
to look at, GET /v1/scene.png?bbox=w,s,e,n (see
emem-field-signals); that is a view,
not a signed artifact.
What ships with it
2 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.
- 28d ago Changed · +2 lines 0d647ffd8c79
- 29d ago Changed · +9 lines · +137 tokens per session 667fdb54e61f
- 1mo ago Changed · -1 lines 45d843c962eb
- 1mo ago Changed · +12 lines d41774a11df3
- 1mo ago First seen · 150 lines · 0 tokens per session scan A 7c622584bab4
emem-field-tokens is a skill published in the GitHub repository Vortx-AI/emem (76 stars, last pushed today), licensed Apache-2.0. It adds 137 tokens to every session and 2,493 once invoked, about $0.0005 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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