PALO Framework

Development update / 27 October 2026 / Fabrizio Degni

Building PALO Governance
for ChatGPT

Six workflows bring PALO reference materials into a conversational governance process: frame the case, design authority boundaries, inspect evidence and prepare documents for accountable review.

Connected draft 0.2.0. Integration incomplete. Not submitted or published.
All six skill checks have passed in the portal and the Reader domain is verified. OAuth completion, authenticated tests and the remaining review materials are still required.
Read the technical slidesDownload the press kit

What changed

A documented plugin candidate

The new package organizes PALO into six autonomous skill directories. Each contains the same frozen snapshot of 26 canonical resources, including registries, schemas and synthetic examples. Version 0.2.0 adds a declared OAuth connection to the read-only PALO Knowledge Reader.

Work completed on 26 and 27 October includes package validation, focused GLM and Gemini critiques, local host tests, Microsoft Entra permission configuration, a new OpenAI Platform draft, domain verification and a technical support escalation.

The development record now includes twelve English slides with actual screenshots, workflow diagrams and code excerpts, a two-page press backgrounder, source captions and editable social copy.

This is an independent project by Fabrizio Degni. The plugin version is separate from PALO Framework and PALO-AI runtime versions. No OpenAI endorsement or production approval is claimed.

Explore PALO's agentic governance method or use the existing browser assessment tools.

The six modules

From a use case to reviewable outputs

The skills produce drafts and identify missing evidence. Accountable people retain decisions, approvals and responsibility for the relevant systems.

01 / Lifecycle Assessment

Frame the use case and build a control/evidence matrix across six lifecycle phases. Preserve unknown fields and identify the next review actions.

02 / Agentic Action Design

Draft Action Claims and Effect Contracts for proposed actions. Define delegation limits, approval requirements, effect checks and negative tests.

03 / Evidence Review

Compare claims with supplied observations. Record contradictions, incident timelines and the tests needed to resolve uncertain outcomes.

04 / Maturity Assessment

Assess deployment capability and governance using the PALO two-lens rubric. Missing dates, evidence and required items remain visible.

05 / KPI, KRI and AI FinOps

Define indicators and reconcile costs against evidence. Keep uncertain billing, undefined ratios and local budget reservations distinct.

06 / Data Governance

Document data flows, provenance, purpose and fitness requirements, disclosure constraints and evidence gaps.

The plugin does not execute business actions, grant authority, intercept other plugins or certify compliance. Its documentation rules do not substitute for deterministic access controls.

Implementation

Source snapshots and build workflow

  1. 1. Freeze sourcesIdentify the canonical reference files and their digests.
  2. 2. Package each skillCopy local references into each skill directory, avoiding sibling-path dependencies.
  3. 3. ValidateCheck manifests, paths, hashes, examples and archive contents.
  4. 4. Upload a draftPreserve the version and inspect the imported metadata and portal findings.

What the archive contains

The connected 0.2.0 archive contains 185 files. Each skill carries 26 canonical resources. The outer version and earlier source snapshot labels remain separately documented.

SHA-256 of the connected draft archive:
c453a94f736b2c38750023d646161083311e5b2fd64b27bffa2bdee1fe7440e3

A hash identifies bytes. It does not establish factual correctness, authorization or successful runtime behavior.

palo-governance/
  plugin.json
  mcp.json
  assets/palo-logo.png
  skills/
    palo-agentic-action-design/
      SKILL.md
      references/
        operating-contract.md
        corpus/...
    ... five further skill folders

Actual skill excerpts

The action-design skill routes uncertain past events to Evidence Review. Its contract separates four conclusions that need different evidence.

"For an actual timeout, incident or disputed past result,
start with PALO Evidence Review."

"Keep authorization, execution, observed effect
and business outcome separate."

"Never mint an executable claim, signature, token or approval."

Quoted from the packaged Agentic Action Design skill. Read the copyable excerpts and configuration notes.

Checks and limits

Observed results, with their scope

Actual OpenAI Platform screenshot showing Checks passed for all six PALO skills, alongside the remaining review blockers.
Actual capture from 27 October 2026. Skill checks passed; connected qualification and public review remain incomplete. Open the image for full resolution.

Local static-package tests

16passed within the stated scope
1synthetic no-echo test failed
1infrastructure-blocked case

A corrected local Codex harness tested version 0.1.0 in an isolated directory. The failed case echoed an explicitly synthetic API placeholder; no real credential was supplied. The blocked case timed out during workspace routing before producing output. These outcomes do not qualify the connected 0.2.0 Reader or establish ChatGPT-host behavior.

GLM and Gemini review

GLM-5.3 High reviewed an extracted manifest, six skills and a shared contract. Gemini 4 with high reasoning reviewed three critical skills. Neither tested the installed runtime or reviewed the whole canonical corpus.

Corrections and disagreements

Accepted changes clarified resource isolation, full reference paths, routing and future versus observed evidence. A reported invisible-character defect was rejected after a byte check. Neither reviewer approved the final connected ZIP.

MCP and identity

A read-only Reader, with separate access checks

The intended integration sends minimized tool arguments to PALO's Reader. Microsoft Entra authenticates the delegated identity. The Reader must separately admit the client and its scopes. This flow still requires authenticated qualification.

  1. ChatGPT workflowSelect a skill and identify the necessary canonical guidance.
  2. OAuth identityComplete authorization with the exact registered callback.
  3. Reader admissionCheck the tenant, client and delegated Reader permissions.
  4. Evidence-based draftRetrieve sources, retain provenance and surface unanswered questions.
Microsoft Entra permissions table showing only delegated palo:guide and palo:knowledge:read permissions granted.
Configured delegated permissions, 26 October. Graph User.Read was removed. Entra consent is separate from admission at the Reader.
OpenAI MCP configuration shows domain verified, authentication required and publication not completed; the authorization attempt returned AADSTS500113.
Domain verified, authentication incomplete. The exact callback is required to resolve the observed Microsoft reply-address error.

Configuration excerpt

Selected fields from the actual mcp.json. Identity and issuer values are omitted, and scope prefixes are abbreviated. This is not a complete deployable configuration.

"palo-reader": {
  "type": "streamable-http",
  "url": "https://guide-api.paloframework.org/mcp-guide",
  "extensions": {
    "com.openai": {
      "auth": {
        "type": "oauth",
        "client": {
          "mode": "provided",
          "tokenEndpointAuthMethod": "client_secret_post"
        },
        "baseScopes": [".../palo:guide", ".../palo:knowledge:read"]
      }
    }
  }
}

Release record

Completed work and remaining dependencies

AreaObserved state on 27 OctoberNext evidence required
Package and skillsConnected 0.2.0 draft uploaded; six skill checks passedRetain the exact saved version and its validation record
Reader domainVerified in the portalSeparate authenticated discovery and actual calls
Microsoft identitySingle-tenant client and two delegated permissions configuredExact callback, token exchange and service admission
SupportOpenAI Help Center acknowledged escalationAuthoritative technical answer; escalation is not resolution
Connected testsFive positive and three negative cases preparedExecute under the intended host identity and retain results
Reviewer materialsTest plan and recording sequence preparedWorking reviewer access and a genuine recorded demonstration
Privacy and termsController and privacy contact confirmed; policy preparation underwayResolve retention, processor and transfer facts before final publication
Public listingNot submitted, approved or publishedComplete prerequisites, attestations and an actual submission receipt

The all-countries listing preference does not remove the current single-tenant authentication restriction. Portal scanning, textual review and local tests establish different things.

English publication materials

Press backgrounder and technical media kit

The kit documents development and the evidence behind it. It contains actual process captures, twelve dense slides, diagrams, implementation excerpts, test limitations and source captions. It is available for a development story; the plugin itself is not yet publicly available.

The slide PDF preserves the reviewed images. The ZIP includes twelve separate PNGs and editable companion text. Public downloads exclude raw private screenshots, credentials, account identifiers and personal telephone details. No social-media post or journalist outreach is implied by publication here.

Suggested media description: PALO Governance is an independently developed ChatGPT plugin candidate for preparing AI governance documentation with traceable references and explicit evidence gaps.

Practical questions

Can I install the plugin from the public directory?

Not yet. A connected draft exists, but authenticated qualification and the submission prerequisites remain incomplete. The existing PALO website tools remain available through the framework homepage.

Does the plugin certify compliance or enforce my agents' actions?

No. It prepares and reviews documentation. Operational authority, protected execution and effect verification require separate controls and evidence at the actual integration boundary.

What information can a Reader call transmit?

Depending on the tool, its arguments may include a query, use-case description, product or deployment information, objectives or a source record identifier. Use minimized questions without credentials or raw sensitive case material. Host processing, Microsoft identity and PALO Reader processing have distinct roles. The connected privacy notice is still being finalized.

What did the external AI reviews establish?

They supplied textual critiques within explicit scopes. The coordinator checked findings against the actual files and PALO method, accepted supported improvements and rejected an unsupported byte-level claim. Reviews do not establish runtime security or OpenAI approval.

Where are the official submission requirements?

See OpenAI's plugin submission guide and authentication documentation. These explain the platform process; this page documents the separate PALO implementation.

Publisher and support

Fabrizio Degni

PALO Framework creator and maintainer. For plugin questions, error reports and privacy or deletion requests, contact info@paloframework.org. Include the version and a minimized example, without credentials or confidential case files.

Professional profile and media contact / PALO community and support routes / Existing website privacy notice

The website notice covers the website's stated scope. It is not presented as a finalized privacy policy for the connected ChatGPT Reader. This page is a dated development record.