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cpp-cpm-engine

by io.github.danafitkowski

collapsed_as_built

Collapsed As-Built / But-For analysis on a post-impact XER.

        Implements AACE RP 29R-03 §3.8 Modeled / Subtractive / Single
        Base method (paired with MIP 3.3 Windows for the dual-method
        gap report per SCL §11.5). Validates a forensic windows
        analysis (MIP 3.3) by independently computing the same
        project drift via subtractive removal of delays from the
        as-built schedule.

        For each delay event, the as-built duration of every
        ``affected_activity`` is shortened by ``impact_days`` (or
        removed entirely if ``removal_method="remove"``), then CPM
        re-runs and the resulting "but-for" finish date is compared
        to the as-built finish. Cumulative pass removes ALL events at
        once for a project-level but-for finish.

        Use this tool when opposing counsel demands a but-for analysis
        or you need a dual-method validation pairing §3.3 (windows) with
        §3.8 (collapsed-as-built). For prospective fragnet insertion
        (MIP 3.7), use ``time_impact_analysis_fragnet`` instead.

        Args:
            as_built_xer_path:    server-side post-impact XER (after delays incurred).
            as_built_xer_content: full text of post-impact XER (alternative for hosted/remote use).
                                  Supply EXACTLY ONE of path/content.
            delay_events: list of event dicts. Each must have
                ``event_id``, ``affected_activities`` (list of
                task_codes), and ``impact_days`` (number). Optional:
                ``removal_method`` ('shorten'|'remove'),
                ``responsible_party``, ``name``, ``description``.
            output_dir: optional output dir for HTML/CSV (tempdir if "").
            project_name: optional override.
            removal_method: global default 'shorten' or 'remove'.
            contractor_filter: when True, exclude contractor-caused
                events from the cumulative pass (owner audit mode).

        Returns:
            {
              "as_built_finish": "YYYY-MM-DD",
              "per_event_results": [{event_id, but_for_finish,
                                      impact_days_collapsed,
                                      duration_removal_basis,
                                      finish_driver_after_removal, ...}, ...],
              # duration_removal_basis discloses WHAT duration was removed
              # and on what basis; finish_driver_after_removal discloses
              # WHAT drives the but-for finish (incl. whether it is bound by
              # the data-date floor) so a reader sees WHY the finish did or
              # did not move across data dates.
              "cumulative_but_for_finish": "YYYY-MM-DD",
              "cumulative_impact_days": int,
              "dual_method_gap": dict | None,
              "output_files": {...},
              "warnings": [...],
              "method": "AACE 29R-03 §3.8 (Modeled/Subtractive/Single Simulation)"
            }

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
output_dirNo
delay_eventsNo
project_nameNo
removal_methodNoshorten
as_built_xer_pathNo
contractor_filterNo
as_built_xer_contentNo

TDQS

A5/5.0
Behavior5/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It explains the subtractive mechanism (shortening or removing affected_activities, CPM re-runs), the cumulative-pass behavior, the dual-method gap report, and even the meaning of output fields such as duration_removal_basis and finish_driver_after_removal. This is unusually transparent for a complex forensic scheduling tool.

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

Conciseness5/5

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

Though long, the description is well-structured into method overview, use guidance, Args, and Returns. Every sentence contributes substantive information—method citation, dual-method validation, event mechanics, alternative tool, parameter semantics, and output rationale. The length is justified by the tool's complexity.

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?

This is a 7-parameter, complex analytical tool with no output schema and no annotations. The description fully covers the algorithm, the validation relationship to forensic_windows_analysis, parameter details, return shape, output files, warnings, and method label. It provides a complete operational picture for an agent to select and invoke the tool correctly.

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?

Schema description coverage is 0%, so the description must compensate, and it does. The Args section explains every parameter, including the critical 'Supply EXACTLY ONE of path/content' mutual-exclusion rule, the required structure of delay_events with optional fields, and the global removal_method default. No parameter is left undocumented or ambiguous.

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 opens with a specific verb and resource: 'Collapsed As-Built / But-For analysis on a post-impact XER.' It clearly defines the method (AACE 29R-03 §3.8 Modeled/Subtractive/Single Base) and contrasts with sibling tools by naming time_impact_analysis_fragnet for prospective work, so it is well differentiated.

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?

It explicitly states when to use this tool: 'Use this tool when opposing counsel demands a but-for analysis or you need a dual-method validation pairing §3.3 (windows) with §3.8 (collapsed-as-built).' It also gives a concrete exclusion with an alternative: 'For prospective fragnet insertion (MIP 3.7), use time_impact_analysis_fragnet instead.'

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