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cpp-cpm-engine

by io.github.danafitkowski

qramm_maturity

QRAMM-aligned maturity reading for an SRA result.

        Places a Schedule Risk Analysis run (from
        ``monte_carlo_p50_p80`` or any equivalent dict) on the five
        named maturity levels of AACE RP 122R-22 (Quantitative Risk
        Analysis Maturity Model), section 3: level 1 Reactive,
        level 2 Ad-hoc, level 3 Centralized, level 4 Dynamic,
        level 5 Adaptive.

        Inputs the SRA inspects (defensively, all keys optional):
          - baseline.percentiles  (lowercase p50 / p80 presence)
          - baseline.config       (iterations, opt/ml/pes %, distribution)
          - baseline.sensitivity  (per-activity tornado rows, on_cp)
          - mitigated             (scenario comparison evidence)
          - risk_register_simulation + risk_register_used
            (Hulett quantified risk register evidence)
          - convergence           (MC diagnostics, required for level 5)

        Use this tool any time you have an SRA result and want a
        maturity reading for a forensic-claim methodology section.
        Note the scope limit the badge carries on every render: AACE
        122R-22 assesses the quantitative-risk capability of an
        ORGANIZATION and states it is guidelines rather than a
        standard, so a reading on one simulation run is CPP's
        placement on the RP's scale, not a QRAMM score. Report it as
        "QRAMM-aligned", never as "per AACE 122R-22".

        Args:
            sra_result: dict from ``monte_carlo_p50_p80``. May be {} -
                the badge degrades to level 1 with the missing
                evidence listed.

        Returns:
            {
              "rp_citation":    "AACE RP 122R-22 ...",
              "scale_max":      5,
              "scale_note":     "... names five levels ...",
              "level":          int (1-5),
              "level_name":     "Reactive" | "Ad-hoc" | "Centralized"
                                | "Dynamic" | "Adaptive",
              "level_label":    "Level 3: Centralized",
              "level_description": what CPP requires of a run there,
              "level_color":    "#xxxxxx",
              "evidence":       ["..." what the SRA had / lacked],
              "gaps_to_next_level": ["..." concrete advance steps],
              "caveat":         scope-limit string
            }

            The keys "tier", "tier_label", "tier_description",
            "tier_color" and "gaps_to_next_tier" are retained as
            aliases carrying the same five-level values.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sra_resultYes

TDQS

A4.9/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description details the tool's behavior: it inspects specific fields (baseline.percentiles, baseline.config, etc.), degrades to level 1 for empty input, and outputs a structured result with evidence and gaps. It also explains the aliases in the return value. This provides comprehensive transparency beyond the simple schema.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with clear sections (purpose, usage, caveat, args, returns) but is somewhat verbose, repeating the level names and containing redundant phrasing. It could be tightened without losing essential information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity and the absence of an output schema, the description fully specifies the return structure, including all keys and their meaning, and the scope limitation. It also covers the input requirements and the degradation behavior, making it self-contained.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

For the single parameter sra_result, the description explains it is a dict from monte_carlo_p50_p80, may be empty, and that an empty dict results in level 1 with missing evidence listed. It also enumerates the specific subfields the tool inspects, greatly enriching the minimal schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function: it 'Places a Schedule Risk Analysis run on the five named maturity levels of AACE RP 122R-22', naming the specific standard and levels. It distinguishes itself from sibling tools by focusing on maturity assessment rather than direct delay or risk analysis.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly says 'Use this tool any time you have an SRA result and want a maturity reading for a forensic-claim methodology section.' It also notes the input source (monte_carlo_p50_p80) and provides a scope-limit caveat, giving clear when-to-use guidance and context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A4.7/5.0
Disambiguation4/5

Each tool targets a distinct analytical deliverable (windows analysis, concurrency matrix, slip velocity, TIA, collapsed as-built, SRA, etc.), and descriptions explicitly cross-reference sibling tools to clarify boundaries. Some pairs like critical_path_validator vs dcma14_health_check and forensic_windows_analysis vs concurrent_delay_matrix share inputs and close conceptual territory, but the stated distinctions are clear enough to prevent misselection.

Naming Consistency4/5

All tool names follow a consistent lowercase snake_case style with descriptive noun phrases (e.g., forensic_windows_analysis, slip_velocity, xer_parser), so there is no mixing of conventions. However, the pattern is not verb_noun and a few names embed acronyms or numbers (dcma14_health_check, monte_carlo_p50_p80, woet_classifier), which is a minor deviation from a fully uniform naming scheme.

Tool Count5/5

13 tools is well-scoped for a forensic CPM/schedule delay analysis server. Each tool covers a distinct method or deliverable—parsing, logic health, DCMA-14, windows analysis, concurrency, slip trends, TIA, collapsed as-built, Monte Carlo SRA, maturity assessment, WOET, path tracing, and an evidence workbench—so every tool earns its place without redundancy.

Completeness5/5

The tool surface comprehensively covers the forensic delay analysis lifecycle: input parsing, schedule logic validation, DCMA-14 health assessment, retrospective windows analysis, concurrency attribution, slip trending, prospective TIA, collapsed as-built, probabilistic SRA, maturity rating, execution classification, and raw-evidence workbench. Minor gaps like schedule editing or cost analysis exist but are outside the server's stated forensic-analysis purpose.

Resources