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cpp-cpm-engine

by io.github.danafitkowski

path_explorer

Logic-trace driver-chain explorer — answers "WHY is this activity critical?" and "WHAT does it drive?".

        Traces driving predecessors backward from a target activity to
        project start (the "why critical" chain) and/or driving
        successors forward to project finish (the "what it drives"
        chain). Detects constraint-driven artificial criticality and
        cites AACE RP 49R-06 when found. Supports multiple parallel
        critical paths (MCPM) and near-critical paths.

        Use this tool when investigating a single activity's logic
        chain. For a project-wide CP / logic health audit, use
        ``critical_path_validator``.

        Args:
            xer_path: server-side path to the schedule XER.
            xer_content: full text of the schedule XER (alternative for
                hosted/remote use). Supply EXACTLY ONE of path/content.
            target_activity_codes: list of task_codes to trace; if
                empty, all CP / near-critical endpoints are traced.
            direction: 'backward' (predecessors), 'forward'
                (successors), or 'both' (default).
            include_near_critical: also trace near-critical endpoints
                (within float band).
            output_dir: optional dir for HTML / CSV / JSON outputs.

        Returns:
            {
              "paths":          [{chain dicts ...}],
              "output_files":   {dashboard, csv, json},
              "project_finish": "YYYY-MM-DD",
              "project_name":   ...,
              "data_date":      ...
            }

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
xer_pathNo
directionNoboth
output_dirNo
xer_contentNo
include_near_criticalNo
target_activity_codesNo

TDQS

A4.8/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden and does so well: it discloses the forward/backward tracing behavior, the AACE RP 49R-06 citation when artificial criticality is detected, the EXACTLY ONE constraint on xer_path/xer_content, and the HTML/CSV/JSON file side effects. It does not disclose error behavior (e.g., invalid XER or missing target activity), which keeps it just shy of a 5.

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?

The description is front-loaded with a punchy two-question hook, followed by dense technical detail, then a clear Args section with one-line meanings per parameter and a Returns JSON example. Every sentence earns its place; the structure makes scanning fast despite the length.

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?

For a complex analysis tool with 6 params, no annotations, and no output schema, the description is remarkably complete: it covers the analysis domain (MCPM, near-critical, artificial criticality), the input constraint, parameter defaults, and the full return shape including output_files, project_finish, project_name, and data_date. The presence of the return structure removes the need for an output schema.

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 fully compensate — and it does. All 6 parameters receive meaningful semantics beyond their bare schema titles: mutual exclusivity for xer_path/xer_content, default behavior for empty target_activity_codes, direction enum values with default, and the float-band meaning of include_near_critical. This is exactly what an agent needs to invoke the tool correctly.

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 opening line uses a specific verb-resource framing ('Logic-trace driver-chain explorer') and immediately answers the two motivating questions: 'WHY is this activity critical?' and 'WHAT does it drive?'. It clearly distinguishes from siblings by scoping to a single activity's logic chain and explicitly naming critical_path_validator as the tool for project-wide audits.

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?

Provides explicit when-to-use guidance: 'Use this tool when investigating a single activity's logic chain. For a project-wide CP / logic health audit, use critical_path_validator.' This names the alternative tool and the differentiating scope, leaving no ambiguity about when it applies.

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