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time_impact_analysis_fragnet

Time Impact Analysis (TIA) — prospective fragnet insertion into a pre-impact baseline schedule. Supports two modes.

        **Single-base mode** (legacy): supply ``baseline_xer_path`` or
        ``baseline_xer_content``. All fragnets are inserted into the
        same shared baseline XER and impact is measured against that
        shared baseline. The result carries a
        ``single_base_disclosure`` warning: one shared baseline is
        AACE 29R-03 MIP 3.6 (Modeled / Additive / Single Base), not
        MIP 3.7 Multiple Base; acceptable when all events share a
        single baseline window.

        **Multi-base mode** (AACE 29R-03 MIP 3.7 Multiple Base):
        supply ``per_event_bases`` — a dict keyed by each fragnet's
        ``id``, with each value a dict containing EITHER
        ``xer_path`` OR ``xer_content`` for that event's
        pre-event contemporaneous baseline. Each fragnet is inserted
        into its OWN base, impact is measured against THAT base's
        pre-event finish, and the result carries
        ``per_event_methodology``, ``per_event_base_count``, and
        ``per_event_bases_used`` (sha256-truncated content hashes for
        audit reproducibility). The cumulative-impact figure carries
        ``cumulative_caveat`` because the sum of events measured
        against different bases is NOT a valid joint impact.

        Exactly ONE of {baseline_xer_path, baseline_xer_content,
        per_event_bases} must be supplied. Multi-base mode errors out
        (returning ``{"error": ...}``) if any fragnet id is missing
        from ``per_event_bases``.

        Use this tool when modeling delay impact prospectively (e.g.
        quantifying RFI / change-order delay before settlement). For
        retrospective windows analysis after the fact, use
        ``forensic_windows_analysis`` (MIP 3.3 windows). For an
        impacted as-planned screen or rebuttal on the unprogressed
        as-planned baseline (MIP 3.6), use ``impacted_as_planned``.

        Args:
            baseline_xer_path:    server-side pre-impact baseline XER
                                  (single-base mode).
            baseline_xer_content: full text of pre-impact baseline XER
                                  (single-base mode, hosted/remote use).
            per_event_bases:      dict {fragnet_id: {"xer_path": "..."}
                                  OR {"xer_content": "<full XER text>"}}
                                  for AACE MIP 3.7 Multiple Base mode.
                                  Example::

                                    {
                                      "F1": {"xer_path": "/tmp/bl_pre_F1.xer"},
                                      "F2": {"xer_content": "<XER text>"},
                                    }

            fragnets: list of fragnet dicts. Each must have:
                - 'id', 'name', 'liability' (responsible party)
                - 'activities': list of {code, name, duration_days,
                                          clndr_id?}
                  (clndr_id is the P6 calendar id, CALENDAR.clndr_id.
                  This tool schedules on a uniform timeline that walks
                  no calendar, so it does not change the result here.)
                - 'ties':       list of {pred, succ, type, lag_days?}
                Optional: 'description'.
            output_dir: output dir for TIA_Report.txt + CSV (tempdir if "").
            project_name: optional override.
            preparer / company: optional, printed in the report header as
                who prepared the analysis. Both are blank unless supplied.

        Returns:
            {
              "report":      path to TIA_Report.txt,
              "impacts_csv": path to TIA_Impact_Details.csv,
              "baseline":    {"project_finish", "critical_count", ...},
              "per_fragnet": [{fragnet_id, name, liability,
                                completion_before, completion_after,
                                impact_days, impact_working_days,
                                affected_activities, status, error}, ...],
              "cumulative_days": int (sum of per-fragnet impacts),
              "cumulative_basis": str (BOTH modes — states the cumulative
                                  figure is the sum of independent
                                  per-fragnet impacts and overstates joint
                                  impact when fragnets share a path),
              "per_event_methodology": str (the method label, or why
                                      nothing was measured),
              "per_event_base_count": int (count of unique base XERs
                                      read; 0 when none could be read),
              "per_event_bases_used": {fragnet_id: sha256_hash8} (multi-base only),
              "per_event_unread": [fragnet_id] (multi-base only: events
                                  whose base could not be read, so not
                                  measured),
              "per_event_requested": int (multi-base only: every event
                                  asked for),
              "not_measured": bool (True when no base could be read: every
                              figure is 0 only because nothing was
                              measured, not a finding of no delay),
              "single_base_disclosure": str (whenever every event
                                      measured shared one base, MIP 3.6),
              "cumulative_caveat": str (multi-base only),
            }
        

Input Schema

NameRequiredDescriptionDefault
companyNo
fragnetsNo
preparerNo
output_dirNo
project_nameNo
per_event_basesNo
baseline_xer_pathNo
baseline_xer_contentNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • addedInput schema / properties / company
      Added value: +{
      +  "default": "",
      +  "title": "Company",
      +  "type": "string"
      +}
    • addedInput schema / properties / preparer
      Added value: +{
      +  "default": "",
      +  "title": "Preparer",
      +  "type": "string"
      +}
  2. First observed

TDQS

A4.9/5.0
Behavior5/5

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

With no annotations the description carries the full burden and does so: it discloses the error path ({"error": ...} when a fragnet id is missing from per_event_bases), the file artifacts written (TIA_Report.txt + CSV), the not_measured flag semantics (zeros mean nothing was measured, not "no delay"), and the two disclosure strings (single_base_disclosure, cumulative_caveat) that warn when a figure is methodologically invalid. It also surfaces the audit-reproducibility hashes and the per_event_unread list, which an agent could not infer from any structured field.

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?

Front-loaded with the mode distinction and the mutual-exclusivity rule, then Args, then Returns, so an agent can stop reading early. The Returns block is lengthy, though that length is largely earned by the absence of an output schema; some of it (restating the cumulative caveat twice) could be tightened.

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 an eight-parameter, nested-object, no-output-schema tool this covers everything an agent needs: which mode to pick, the exact dict shape per mode, the failure mode, and the semantics of every returned field including the ones that guard against misreading zeros or summing non-joint impacts. Nothing material is left to inference.

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 coverage is 0% and the description fully compensates, documenting all eight parameters including the nested fragnet contract (required id/name/liability, activities with code/name/duration_days/clndr_id, ties with pred/succ/type/lag_days, optional description) and a worked per_event_bases example. It even explains that clndr_id is inert for this scheduler, which is meaning the schema cannot convey.

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?

Names a specific technique and operation — prospective fragnet insertion into a pre-impact baseline XER — and enumerates the two execution modes (single-base vs AACE MIP 3.7 multiple-base) with the exact parameters each requires. The opening line alone distinguishes it from forensic_windows_analysis and impacted_as_planned without opening a schema.

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?

Gives explicit positive guidance ("modeling delay impact prospectively, e.g. quantifying RFI / change-order delay before settlement") and routes two named siblings to their own conditions (retrospective windows → forensic_windows_analysis; unprogressed as-planned rebuttal → impacted_as_planned). It also states the hard constraint that exactly one of the three baseline parameters must be supplied, which is the main invocation pitfall.

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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