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 equinor/neqsim-community-skills --skill neqsim-technology-fmirrgit clone --depth 1 https://github.com/equinor/neqsim-community-skillsWrote 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/equinor/neqsim-community-skills/neqsim-technology-fmirr)<a href="https://agentmods.dev/skills/equinor/neqsim-community-skills/neqsim-technology-fmirr"><img src="https://agentmods.dev/badge/skills/equinor/neqsim-community-skills/neqsim-technology-fmirr/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/equinor/neqsim-community-skills/neqsim-technology-fmirr"><img src="https://agentmods.dev/badge/skills/equinor/neqsim-community-skills/neqsim-technology-fmirr.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 | $0.00088 | $0.01541 |
| Opus 5.5 | $0.00035 | $0.00616 |
| Sonnet 5.5 | $0.00018 | $0.00308 |
| Haiku 4.5 | $0.00009 | $0.00154 |
Grade A, and why
neqsim-technology-fmirr 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 10d 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 — 146 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Technology FMIRR (Failure Mode Identification and Risk Ranking)
Use this skill to keep and rank the failure-mode register of a technology that
is being qualified. The register is the basis for defining and prioritising the
qualification activities: every critical failure mode must trace to a
qualification activity (the TEST column) and every re-rating must trace to
evidence.
When to Use
- After
neqsim-technology-assessmenthas identified novel elements (category 2b-4) and before the qualification plan is written. - To prepare or review the output of an FMIRR workshop with an expert panel.
- To repeat the FMIRR as test results and mitigations change the risk.
- To feed the FMIRR chapter of
neqsim-technology-assessment-report.
It does not replace the workshop. Failure modes, causes and ratings must come from a panel covering the needed disciplines.
Inputs
technologyname.entries: one per failure mode withid,item(failed item or component),function,failure_mode,failure_mechanism,failure_mechanism_class,failure_cause,failure_cause_class,detection,consequence_text,consequence_class(1-5),probability_class(1-5),comments,qualification_test(link to the qualification plan),lifecycle_phase,novelty_category.- Optional: a custom 5x5 matrix and the high-consequence floor setting.
Outputs
rowswith the computed risk (Low,Medium,High) and acriticalflag.summary: counts per risk level, critical ids ranked, critical modes with and without a qualification test.risk_matrix: counts per probability and consequence cell.findings: warnings and gaps (mixed terminology, missing mechanism, critical modes without a test or detection, life-cycle phases not covered).history: previous ratings with their basis;iterationnumber.
Engineering Method
- Scope. Take the novel elements from the technology assessment and their life-cycle phases (design, fabrication, transport, installation, commissioning, operation and maintenance, decommissioning).
- Identify failure modes per element and phase. Keep four separate fields:
- Failed item: the component that fails.
- Failure mode: how it fails (for example external leakage, fails to close).
- Failure mechanism: the physical process (mechanical, material, instrumentation, electrical, external influence, miscellaneous).
- Failure cause: why (design, fabrication/installation, operation/maintenance, management, miscellaneous; include human error). Use the equipment-specific ISO 14224 failure-mode tables where they exist.
- Rate consequence for the system as specified, without safeguards that are not yet adopted. Use the highest class across people, environment, delay/downtime and reputation. Define the scale for the case.
- Rate probability with qualitative classes early; replace by evidence (tests, analysis, documented experience) as it arrives. If evidence is lacking, be conservative, more so for higher novelty.
- Rank risk with the matrix. Medium and High are critical and must be covered by the qualification plan. Low modes stay in the register. The high-consequence floor keeps class-5 consequences at Medium or above so that low probability does not dismiss them.
- Link tests. Give each critical mode a qualification activity and a detection method.
- Re-rate and repeat. Record the basis for every change, start a new iteration at each qualification milestone, and never delete a mode.
What ships with it
7 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.
- 10d ago First seen · 146 lines · 88 tokens per session scan A c5ed61500594
neqsim-technology-fmirr is a skill published in the GitHub repository equinor/neqsim-community-skills (4 stars, last pushed today), licensed Apache-2.0. It adds 88 tokens to every session and 1,541 once invoked, about $0.0004 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 2026-10-28.
neqsim-technology-fmirr compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| neqsim-technology-fmirrequinor/neqsim-community-skills | Skill | 4 | today | Apache-2.0 | A | 88 | Claude Code, Codex |
| instrument-data-to-allotropeanthropics/knowledge-work-plugins | Skill | 35k | 3d ago | Apache-2.0 | A | 123 | Claude Code |
| exploratory-data-analysisK-Dense-AI/scientific-agent-skills | Skill | 56k | 4d ago | MIT | A | 83 | Claude Code |
| matlabK-Dense-AI/scientific-agent-skills | Skill | 56k | 4d ago | MIT | A | 44 | Claude Code |
| phylogeneticsK-Dense-AI/scientific-agent-skills | Skill | 56k | 4d ago | MIT | A | 71 | Claude Code, Codex |
| research-engineerdavila7/claude-code-templates | Skill | 33k | yesterday | MIT | A | 43 | Claude Code, Codex |
| mapping-to-snomedmaziyarpanahi/openmed | Skill | 5.8k | yesterday | Apache-2.0 | A | 205 | Claude Code |