neqsim-continuous-task-improvement

neqsim-continuous-task-improvement is a skill for Claude Code, Codex from equinor/neqsim. It costs 101 tokens per session (4,560 once invoked), scanned A, original, Apache-2.0.

A set of instructions for keeping NeqSim engineering tasks active after their first report. NeqSim is engineering software; these instructions use repeated checks, new evidence, key performance measures, and reviewable improvement records.

In plain words
What is it for?
Use it to schedule task cycles, solve toward a goal or convergence, start from a Word or Markdown brief, and test whether a monitor detects expected faults without false alarms.
Why use it?
It replaces one-time reporting with small, resumable cycles that can detect drift or changed plant data. It keeps automated work separate from human decisions about approving a new baseline.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to schedule task cycles, solve toward a goal or convergence, start from a Word or Markdown brief, and test whether a monitor detects expected faults without false alarms.

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Install with agentmods
npx agentmods add skills/equinor/neqsim/neqsim-continuous-task-improvement
Install

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.

Any agent
npx skills add equinor/neqsim --skill neqsim-continuous-task-improvement
Clone the repo
git clone --depth 1 https://github.com/equinor/neqsim

Made for: Claude Code, Codex.

Wrote 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.

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README.md
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Per session 101 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,560 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00101 $0.04560
Opus 5.5 $0.00040 $0.01824
Sonnet 5.5 $0.00020 $0.00912
Haiku 4.5 $0.00010 $0.00456

Measured yesterday against content hash 54597cc99f0b, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

neqsim-continuous-task-improvement 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 yesterday.

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.

.github/skills/neqsim-continuous-task-improvement/SKILL.md · 285 lines

How it starts

The opening of the file, as written. The whole thing — 285 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Continuous Task Improvement (Living Tasks)

A normal task ends with a report. A living task keeps a continuous/ folder next to the normal three steps and is improved by cycles: small, resumable, auditable runs that pull new evidence, recompute KPIs, detect drift, update an improvement ledger and — only on a trigger — ask an agent to look. The engineer promotes a reviewed cycle to the new baseline. Nothing in the old task changes.

Principle: program the loop, prompt the exceptions. The runner makes no LLM calls; agents run only when a trigger fires; people decide.

When to use

Need Command
Keep a finished task up to date (daily, on a server or on demand) task-living then task-schedule --install
Solve until the goal is met, or until improvement is marginal task-solve --until goal / --until converged
Resume after closing VS Code, rebooting or changing machine task-status <task> then task-resume <task>
Reassess after a datasheet, drawing, standard, measurement or model changes task-status <task> then task-update <task>
Issue a reviewed standalone Word/HTML delivery Promote the validated cycle, then task-report <task> --final --reviewer NAME
Start from a Word/Markdown brief neqsim new-task "title" --prompt-file brief.docx then task-living
Prove a monitor finds the faults it should (and no others) task-backtest --start ... --end ...
Try everything without company data task-reference-case <folder>

All commands run through the shared interpreter: <python-executable> devtools/neqsim_cli.py task-<command> ... (or neqsim task-<command>). <task> may be a path or a folder name inside the task root (neqsim --show-task-root); task-status and task-reference-case default to the task root when no folder is given.

Workflow

  1. Make it living (never overwrites):
    neqsim task-living <task> --brief brief.docx
    
    Creates continuous/cycle_plan.yaml, a draft goal.yaml compiled from the brief, baseline/ from results.json key results, a ledger seeded from recommendations, and a continuous: block in study_config.yaml.
  2. Edit the plan — sources (adapter + options), scripts (task-local stage functions), KPIs, drift signals, triggers, stages, solve settings, backtest expectations. See the template written by task-living.
  3. Confirm the goal — fill objective.metric/direction/target and set confirmed_by. task-solve refuses an unconfirmed goal (--allow-unconfirmed for experiments only).
  4. Backtest before scheduling — replay archived data with a simulated clock:
    neqsim task-backtest <task> --start 2025-10-02 --end 2026-09-30 --repeat
    
    Report: detected / missed expected events, delay, false alarms per month, reproducibility. Written to continuous/backtests/<run>/; live state is untouched.
  5. Resume before starting fresh work — neqsim task-status <task> is the five-second persisted view. If it reports resumable work, run neqsim task-resume <task>. The task folder, not prior chat, is authoritative.
  6. Process evidence changes — map evidence globs to affected stages and conclusions under evidence.rules (match, stages, affected kpis, and conclusions); use neqsim task-update <task>. Mapped changes rerun only the affected stages and declared dependencies while invalidating affected KPIs and retaining unaffected ones. An unmapped path fails closed to the full plan.
  7. Run cycles — neqsim task-cycle <task> (monitor) or schedule it: neqsim task-schedule <task> --daily 05:00 --install (Windows Task Scheduler; the cron line is printed for Linux servers).
  8. Review and promote — read continuous/LIVING_REPORT.md (the always-current view) and cycles/<id>/digest.md, decide ledger items (task-ledger <task> set OPP-0002 accepted --by NAME), then neqsim task-promote <task> <cycle-id> --reviewer NAME.
  9. Finalize explicitly — only after the accepted result is promoted and evidence is current, run neqsim task-report <task> --final --reviewer NAME. This uses the canonical Task Solver generator and writes an immutable FR-### Word/HTML delivery plus hashes and audit references.

Read the full file on GitHub · 285 lines

Changes

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.

  1. yesterday Changed · +19 lines 54597cc99f0b
  2. 6d ago Changed · +5 lines ea239fba2546
  3. 8d ago Changed · +25 lines · +1 tokens per session 7f3f51b1fc09
  4. 9d ago Changed · +8 lines f902fabfcd05
  5. 12d ago Changed · +50 lines fd105cf414b3
  6. 20d ago First seen · 178 lines · 100 tokens per session scan A 4e75549c194f

Subscribe to this mod's changes

neqsim-continuous-task-improvement is a skill published in the GitHub repository equinor/neqsim (156 stars, last pushed today), licensed Apache-2.0. It adds 101 tokens to every session and 4,560 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 2026-09-27.

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