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Third Party Manager Scorecard Review

Owner-oversight review of third-party property manager performance. Scores against the PMA's service standards and the overlay's rubric, computes adherence metrics, flags audit findings, produces the scorecard memo and the TPM-facing communication draft. Runs monthly per property and quarterly per PMA. Material performance gaps and any PMA amendment or termination are gated.

What this skill does

Third Party Manager Scorecard Review is an A.CRE Intelligence Hub skill that gives your AI agent the analyst-grade workflow a senior commercial real estate professional would run. Owner-oversight review of third-party property manager performance. Scores against the PMA's service standards and the overlay's rubric, computes adherence metrics, flags audit findings, produces the scorecard memo and the TPM-facing communication draft. Runs monthly per property and quarterly per PMA. Material performance gaps and any PMA amendment or termination are gated. Owner-oversight review of third-party property manager performance. Scores against the PMA's service standards and the overlay's rubric, computes adherence metrics, flags audit findings, produces the scorecard memo and the TPM-facing communication draft. Runs monthly per property and quarterly per PMA. Activate it inside ChatGPT, Claude, Manus, or OpenClaw by saying something like "Use the Third Party Manager Scorecard Review skill" — the Hub routes the request to this skill and the underlying primary-source CRE data feeds backends automatically.

How you'll use it

"Use the Third Party Manager Scorecard Review skill"

Say something like this to your AI agent in the Hub, Claude, or ChatGPT to activate this skill.

Skill activation rules

Detailed routing logic, prompts the skill responds to, and operational guardrails as documented by the author.

Owner-oversight review of third-party property manager performance. Scores against the PMA's service standards and the overlay's rubric, computes adherence metrics, flags audit findings, produces the scorecard memo and the TPM-facing communication draft. Runs monthly per property and quarterly per PMA. Material performance gaps and any PMA amendment or termination are gated.

What's inside

Third-Party Manager Scorecard Review

Workflow purpose

Hold the third-party manager accountable with a defensible, data-driven scorecard anchored to the PMA and the operating outcomes the owner expects. Surface material performance gaps early so remediation is an ordinary…

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Third-Party Manager Scorecard Review

Workflow purpose

Hold the third-party manager accountable with a defensible, data-driven scorecard anchored to the PMA and the operating outcomes the owner expects. Surface material performance gaps early so remediation is an ordinary conversation rather than a rupture. Ensure every audit finding is tracked to resolution. Route PMA amendment or termination through the correct approval path.

This pack is flagship-depth. It is where ownership's oversight layer converts a TPM's operating output into an ownership-grade judgment. It is also where PMA integrity lives: service standards, reporting cadence, data quality, approval responsiveness, and audit posture.

Trigger conditions

Full instructions and any reference files ship in the .skill bundle.

Bundle structure
third-party-manager-scorecard-review/
└── SKILL.md                           # Required: instructions + metadata

Who built it

With contributions from Avi Hacker.

How to run it

Not in the Hub? Download the .skill bundle above and follow the A.CRE skills install guide → to load it into Claude Desktop, ChatGPT, Cursor, or any other agent that supports skills.

Already in the Hub. If you're an AI.Edge Pro or A.CRE Accelerator member, this skill is bundled into the A.CRE Intelligence Hub direct connector (MCP server) — just ask your agent.

About this skill

Third-Party skill. This skill is redistributed under the Apache-2.0 license and is not authored or endorsed by Adventures in CRE. Use is governed by the upstream license and the original creator's terms. Original attribution: Mario Urquia (link) and contributors (Avi Hacker).