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-research-grade-citationgit 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-research-grade-citation)<a href="https://agentmods.dev/skills/vortx-ai/emem/emem-research-grade-citation"><img src="https://agentmods.dev/badge/skills/vortx-ai/emem/emem-research-grade-citation/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-research-grade-citation"><img src="https://agentmods.dev/badge/skills/vortx-ai/emem/emem-research-grade-citation.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 | $0.00147 | $0.01911 |
| Opus 5.5 | $0.00059 | $0.00764 |
| Sonnet 5.5 | $0.00029 | $0.00382 |
| Haiku 4.5 | $0.00015 | $0.00191 |
Grade A, and why
emem-research-grade-citation 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/recall -H 'content-type: application/json' \ How it starts
The opening of the file, as written. The whole thing — 131 lines — stays where its author put it; the contents beside it link to each section on GitHub.
emem-research-grade-citation
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 signed fact proves who served which bytes. It does not by itself say what quantity those bytes estimate. A citation a reviewer can use needs both: the token that pins the bytes, and a sentence that names the estimand. This skill fills in the second from the fields emem does return, and says where the fields stop.
What a fact carries
curl -sf -X POST https://emem.dev/v1/recall -H 'content-type: application/json' \
-d '{"cell":"defi.zb493.zezo.zcb35","bands":["copdem30m.elevation_mean","esa_worldcover.lc_2021"]}' \
-o facts.json
jq -c '.facts[] | {band, value, unit, observed_at, fn: .derivation.fn_key,
args: .derivation.args, source: .sources[0].id, token: .memory_token}' facts.json
jq '.spatial_basis' facts.json
Recorded on 2026-09-28 in Bengaluru:
{"band":"copdem30m.elevation_mean","value":918.637939453125,"unit":"m","observed_at":"2021-04-30T00:00:00Z",
"fn":"copernicus_dem_30m_aws_pixel@1","args":[12.97679089393182,77.59005965949524,"reader=cog-pixel-floor@2"],
"source":"https://copernicus-dem-30m.s3.amazonaws.com/Copernicus_DSM_COG_10_N12_00_E077_00_DEM/...DEM.tif",
"token":"emem:fact:defi.zb493.zezo.zcb35:gzfrgbobepbuxzgizwp2a4if6nlsgporsezb7hfthgds6pfnapka"}
| Field | Tells you |
|---|---|
value, unit |
the number and its unit, as signed |
derivation.fn_key |
the materialiser and its version (@1) |
derivation.args |
the sampled coordinates, tile or scene id, release, and the reader stamp (reader=cog-pixel-floor@2: which pixel a coordinate maps to) |
sources[] |
the upstream file or release, with a listing hash where the publisher rotates releases |
observed_at, tslot |
when the source observed it, not when emem read it (signed_at) |
spatial_basis |
that the value is a sample of the source pixel, not an average over the cell |
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 7b5609799209
- 29d ago First seen · 129 lines · 147 tokens per session scan A 641ce560a96a
emem-research-grade-citation is a skill published in the GitHub repository Vortx-AI/emem (76 stars, last pushed today), licensed Apache-2.0. It adds 147 tokens to every session and 1,911 once invoked, about $0.0006 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 2026-09-29.
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