neqsim-professional-reporting

NeqSim Professional Reporting Skill

What separates "an answer" from a professional deliverable: traceability, unit hygiene, citation discipline, structured results.json, and a report narrative that matches the way senior engineers communicate.

When to Use

• Finalizing any task report under task_solve/
• Building Jupyter notebook deliverables (study-grade, not exploratory)
• Producing FEED-quality memos, technical notes, or design basis documents
• Any output that will be read by a reviewer, client, or auditor

Principle 1 — Traceability Chain (MANDATORY)

Every figure → discussion → result must be linkable both ways:

results.json[key] ──→ discussed in §3.2 ──→ shown in figures/fig_03.png
              ↑                                        ↓
              └──── caption references key ────────────┘

Required JSON schema fragment:

{
  "figures": [
    {
      "id": "fig_03",
      "path": "figures/fig_03_phase_envelope.png",
      "caption": "Phase envelope at 95 mol% methane composition.",
      "discussed_in": "section_3_2",
      "linked_results": ["dew_point_T_K", "cricondentherm_K"]
    }
  ],
  "results": {
    "dew_point_T_K": {"value": 244.3, "unit": "K", "source": "neqsim TPflash"},
    "cricondentherm_K": {"value": 254.8, "unit": "K", "source": "calcPTphaseEnvelope"}
  }
}

Principle 2 — Executive Summary Structure

Every report opens with a 1-page executive summary built from these blocks (in order):

1. Objective — one sentence: "Determine X for Y under Z conditions."
2. Method — one sentence: "Using EOS / equipment model / standard X."
3. Key result — 2–3 numbers with units and uncertainty (P10/P50/P90 if Monte Carlo run)
4. Conclusion — one sentence with the engineering decision
5. Limitations — 1–2 bullets on key caveats

The executive summary and problem description are report-blocking sections. Do not leave template text such as "[Replace with ...]" or "[Auto-populated ...]" in a final HTML/Word report. If results.json and task_spec.md contain enough information, generate these sections automatically from those sources; otherwise pause and fill the missing source material before finalizing.

Principle 3 — Units & Significant Figures

• State units everywhere — bara, °C, kg/h, MJ/Sm³, never bare numbers
• Significant figures match accuracy — 3 sig fig for thermo; 2 for cost; never more than 4 unless source is exact
• Consistent within report — pick one set (SI, °C/bara) and don't switch
• Standard conditions — always disclaim Sm³ basis (15 °C / 1.01325 bara, or 20 °C, or 0 °C — they differ ~5%)
• Stream tables — use standardized columns: name, T [°C], P [bara], ṁ [kg/h], xi [mol%]

Principle 4 — Citations

For every standard, correlation, or vendor source:

Per **API 521 §5.15 (2020)**, fire heat input is Q = C × F × A_w^0.82 [API521-2020].

References:
[API521-2020]  API Standard 521, Pressure-Relieving and Depressuring Systems, 7th ed., 2020.
[NORSOK-P-100] NORSOK Standard P-100, Process Systems, Rev. 3, 2018.
[Turton-5e]    Turton et al., Analysis, Synthesis and Design of Chemical Processes, 5th ed., 2018.

Avoid: "as is well known", "industry standard says". State the source.

Principle 5 — Math (KaTeX)

For documents rendered through Jekyll docs site:

Inline: the acentric factor $\omega$ affects $\alpha(T_r, \omega)$.

Display:
$
P = \frac{RT}{v - b} - \frac{a(T)}{v(v + b)}
$

Never use \[ ... \] or \( ... \) — they are stripped by markdown processors.

Principle 6 — Figure Quality

Every plot must have:

• Axis labels with units — Pressure [bara], not P
• Title — what is shown, at what conditions
• Legend — even with 1 series (states what is plotted)
• Grid — minor or major, increases readability
• Annotation of key values — pinch point, surge line, design point
• Resolution — ≥ 150 DPI for embedding, vector (SVG/PDF) preferred for line plots

fig, ax = plt.subplots(figsize=(8, 5), dpi=150)
ax.plot(T, P, label="Phase envelope")
ax.scatter([T_op], [P_op], color="red", marker="x", s=80, label="Operating point")
ax.set_xlabel("Temperature [K]")
ax.set_ylabel("Pressure [bara]")
ax.set_title("Phase envelope — sales gas, 95% C1")
ax.legend(loc="best", fontsize=9)
ax.grid(alpha=0.3)
fig.tight_layout()
fig.savefig("figures/fig_03_phase_envelope.png", dpi=150)

Principle 7 — Uncertainty Disclosure

Standard / Comprehensive task reports MUST include:

• Monte Carlo with P10 / P50 / P90 for any economic or reservoir-tied output
• Tornado diagram ranking inputs by impact on the key output
• Sensitivity scan to top-3 driving inputs
• AACE class declaration for any cost number (Class 5: ±100%, Class 4: ±50%, Class 3: ±30%)

Quick tasks may skip MC but still must state qualitative uncertainty.

uncertainty sub-schema (validated by the gate). p10, p50, p90 must be numeric and monotonically ordered (p10 ≤ p50 ≤ p90); a non-numeric or out-of-order percentile is a hard error in both TaskResultValidator and devtools/validate_task_results.py. Include method and n_simulations (≥ 200 when the Monte Carlo loop runs full NeqSim simulations).

Principle 8 — Risk Section

Standard / Comprehensive reports include a risk register scored on a 5×5 matrix (probability × consequence) per ISO 31000 / NORSOK Z-013, with mitigation actions. Use neqsim-process-safety classes.

Principle 9 — Benchmark Validation

Every numerical result must be benchmarked against an independent reference:

State the benchmark in the report. No benchmark = result is provisional.

benchmark_validation sub-schema (validated by the gate). Emit it as a JSON array (or an object wrapping benchmarks/cases). Each entry must carry:

Both TaskResultValidator (Java) and devtools/validate_task_results.py (the CI gate) now check this structure, so a malformed benchmark block fails the gate instead of crashing the report generator.

Principle 9b — Evidence Matrix for Safety Studies

For safety-critical studies, especially trapped-liquid fire rupture, relief, depressurization, MDMT, and consequence handoffs, include an evidence matrix and assumptions/gaps register in both results.json and the report:

Do not hide missing material certificates, flange/gasket/bolt ratings, fire-study heat fluxes, or acceptance criteria. A study may still provide screening results, but the executive summary must state when final design is blocked by evidence gaps.

Safety-critical reports must include a front-page readiness badge or equivalent plain-text label: NOT_READY, SCREENING, or DESIGN_GRADE. The label must be backed by visible blockers/findings and must not imply sign-off when any controlled-document, historian/tagreader, pressure-profile, or material basis is missing or unreviewed.

For script-backed studies, study_config.yaml is the source of truth for whether notebooks are required. A report generator should not warn about missing planned notebooks when the configuration explicitly says notebooks.required: false, execution_required: false, and execution_engine: script.

Before report generation, check consistency between task_spec.md, analysis scripts/notebooks, results.json, and the report narrative. Method changes such as replacing a reconstructed depressurization profile with a directly exported dynamic NeqSim profile must be reflected everywhere, including capability_assessment.md, analysis.md, and neqsim_improvements.md when workflow gaps were found.

Principle 10 — results.json Master Schema

{
  "task_id": "2026-04-26_my-task-slug",
  "task_type": "B-process",
  "scale": "standard",
  "objective": "...",
  "method_summary": "...",
  "agent_workflow_plan": {
    "discovery": {"skill_search": "devtools/skill_search.py", "agent_search": "step1_scope_and_research/agent_plan.json"},
    "agents_used": [ {"name": "...", "repo": "neqsim|community|enterprise", "role": "...", "loads_skills": ["..."]} ],
    "workflow_type": "single_agent | composition_pattern | declarative_workflow",
    "workflow": "e.g. process.model -> mechanical.design, or composeWorkflow id / harness study name",
    "rationale": "why this composition utilizes the needed functionality"
  },
  "key_results": {
    "primary_metric": {"value": 1.23, "unit": "MW", "uncertainty": "±10%"},
    "...": {}
  },
  "results": { "...": "..." },
  "figures": [ { "id": "fig_01", "path": "...", "caption": "...", "discussed_in": "...", "linked_results": [] } ],
  "tables": [ { "id": "tbl_01", "path": "...", "caption": "..." } ],
  "uncertainty": { "method": "Monte Carlo n=10000", "P10": ..., "P50": ..., "P90": ... },
  "risks": [ { "id": "R1", "description": "...", "P": 3, "C": 4, "score": 12, "mitigation": "..." } ],
  "standards_applied": ["API 521-2020", "NORSOK Z-013"],
  "benchmarks": [ { "what": "PSV area", "reference": "API 520 Ex 5", "delta_pct": 1.2 } ],
  "evidence_matrix": [ { "document": "...", "value": "...", "used_for": "..." } ],
  "assumptions_gaps": [ { "gap": "...", "default_used": "...", "impact": "...", "action": "..." } ],
  "limitations": ["..."],
  "next_actions": ["..."]
}

Common Mistakes

Validation Checklist (RUN BEFORE FINALIZING)

• Executive summary present, 1 page max
• Every figure referenced in text and has caption + units
• Every result in results.json traceable to figure or table
• Units consistent and labelled everywhere
• Standards cited by document number, year, section
• Uncertainty (P10/P50/P90) for every economic / reservoir result
• Risk register with 5×5 scoring (Standard+ tasks)
• Benchmark comparison ≤ 5% deviation OR justified
• AACE class declared for cost numbers
• python devtools/consistency_checker.py passes
• Limitations section honest about model assumptions
• Next-actions list at end (what would close the gaps)

Related Skills

• neqsim-regression-baselines — locking baselines for traceability
• neqsim-input-validation — catching bad inputs early
• neqsim-standards-lookup — citation lookup
• neqsim-process-safety — risk-register schema
• neqsim-trapped-liquid-fire-rupture — evidence matrix, rupture/PFP results, and source-term handoff reporting