ChatGPT Plugin

Forward Deployed

Forward-deployed AI skills

Brand: Forward Deployed

Category: AI
Primary Subcategory: AI Product Spec & Build Planning

Integration details

Description

Develop valuable AI use cases and carry them from customer discovery into design, engineering delivery and adoption. Forward Deployed provides 16 skills for FDEs, deployment leads, consultants and builders, covering workflow redesign, solution architecture, enterprise integration, context engineering, evaluation, engineering handoffs and value measurement. In supported ChatGPT hosts, keep the engagement beside the conversation, select a source or requirement to give ChatGPT precise context, and mention saved records from the composer. Native forms help review proposed changes and configure experiments. Compare before and after values and see which requirements, delivery work and rehearsals a change affects. Field Lab tests a declared workflow and lets you branch from a recorded step. Try an editable AI deployment sample without saving; sign in when you choose to save work. Export to portable files or prepare an engineering handoff for your Git repository. Host feature availability varies; workspace controls provide a fallback. The skills also work independently with your existing tools.

Integration type: Plugin
Verification status: Not applicable
Platform: ChatGPT
Category: AI
Primary Subcategory: AI Product Spec & Build Planning
Secondary Subcategories: None listed
Brand: Forward Deployed
Access: Account required
First tracked: 2026-10-27
Tool count: 25
Market: US

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Primary Subcategory

Competing in ChatGPT AI Product Spec & Build Planning

View Category

Listed in alphabetical order

Primary Subcategory

Acceptance Criteria ExtractorComing soonGet notified

AI Task Brief BuilderComing soonGet notified

AI Workflow PlannerComing soonGet notified

airfocusComing soonGet notified

BizlinAIComing soonGet notified

Forward DeployedComing soonGet notified

Tools

25 tools agents can invoke

Use to retain selected meeting notes, source passages or operator observations in this engagement. Read authorized Meetings or other sources through the host first; this tool does not access meetings itself. Preserve source links, origin IDs and preliminary/final status.
add_evidence
Apply one declared state transition to an existing Field Lab run. Only set, increment and append operations can change the simulated JSON state, after typed input and comparison checks. actionId selects a transition stored in the scenario, not an external tool or API. No external business action or source code executes. Reuse intentId only for a retry of the same transition and inputs.
act_in_rehearsal
Apply only the user-selected changes, reject them, or revise their fields for another review. Accepted changes apply together and preserve earlier versions. Read current proposal and engagement versions first.
review_changes
Use when the user wants to test another set of assumptions. Choose a point in a recorded rehearsal, edit typed observable conditions, then confirm a new branch. Only simulated workspace state changes.
experiment_with_form
Read the identity associated with this connection.
get_profile
Store a declarative Field Lab scenario: initial JSON state, typed inputs, comparison conditions, state edits and outcome checks. Allowed state edits are set, increment and append. Named scenario actions label simulated transitions; they are data, not registered tools or external operations. No source code is accepted or executed. Record the model assumptions.
define_rehearsal
Use to capture behavior and acceptance examples for an opportunity, linked to discovery evidence. Distinguish proposed requirements from confirmed ones.
define_requirement
Use to save or refine a concrete service: who benefits, how work happens today, what becomes possible and how to judge it. Link exact source passages; keep proposed targets and assumptions explicit. The host supplies the analysis.
shape_opportunity
Use to export the current workspace as a portable ZIP with readable documents, requirements, source references, rehearsals and a checksum manifest. Selected evidence is included unless disabled. Does not publish or save to another service.
export_engagement
Find saved discovery, service, requirement, delivery and rehearsal records to mention in a conversation. Searches only the connected identity’s saved engagements.
search_records
Use to find an existing engagement before creating another. Returns only workspaces available to the connected identity.
list_engagements
Use when a rehearsal has reached an outcome or cannot proceed. Checks the recorded state against its outcome criteria and invariants, with links to the requirement versions tested.
finish_rehearsal
Use to show the interactive workspace or Field Lab. Data tools can be used without opening the interface.
open_studio
Use to save one piece of build work, its intended outcome, owner and linked requirements. Marking work done records implementation status; rehearsal evidence is computed separately.
plan_delivery
Use when the user wants to save this engagement to their own Git repository. Returns a namespaced set of text files and commit details for the host’s connected Git tools. It does not create a repository or push. Confirm the destination; default new repositories to private. Preserve unrelated files.
prepare_git_export
Stage explicit changes to discovery evidence, opportunities, requirements or delivery work for user review. Include stable IDs for new records and current versions for updates. No proposed record is applied until accepted.
propose_changes
Use to understand the proposed services, evidence, requirements, work and rehearsals before continuing. Returns the current revision for subsequent writes.
get_engagement
Read a Field Lab run’s observable JSON state and the declared data transitions available at that step. This is a read-only inspection of a simulation; it performs no scenario action, external operation or tool discovery. Private scenario fields and outcome checks are withheld from the candidate view.
observe_rehearsal
Use to read a saved source, including the exact historical version cited by a requirement or opportunity.
fetch
Use when the user wants to review a discovery, service or delivery change proposal. Shows each proposed change and its impact, collects accept/reject choices, then asks for explicit confirmation. Leaves pending changes untouched. Use the workspace to revise fields.
review_with_form
Use only when the user chooses to save this workspace on Forward Deployed. Requires sign-in. Creates a hosted copy of the supplied workspace snapshot; stateless work does not need this tool.
save_engagement
Use to find relevant passages in the connected user’s saved engagement evidence. This searches saved material, not external meetings or the web.
search
Use to try a proposed service. Creates an independent run of the selected scenario version. Continue by observing and taking actions toward the stated goal.
start_rehearsal
Use when the user wants a persistent workspace for developing a useful service. Record the ambition and customer. A short standalone question does not need an engagement.
create_engagement
Use to branch from a selected point in a run. Keep the original; optionally change explicit state assumptions to explore a different case. atStep is the number of existing timeline entries retained.
fork_rehearsal

FAQs

Forward Deployed ChatGPT Plugin FAQ

How the directory, categories and Discoverability Score work.

Read the methodology

How do I improve Forward Deployed's ChatGPT Plugin discoverability?

The levers are the listing surface agents actually read: names, descriptions, keywords, tool metadata, and registry health. Which lever matters depends on where discovery breaks, which is what continuous measurement shows.

What are Forward Deployed alternatives on ChatGPT?

As of 2026-10-28, Forward Deployed competes with Acceptance Criteria Extractor, AI Task Brief Builder, AI Workflow Planner, airfocus, BizlinAI, ChatPRD, Codelit, DBBS Project Scope Generator and 12 more in ChatGPT AI Product Spec & Build Planning, ranked by public Discoverability Score.

Where is this profile measured?

This profile uses the geography attached to the latest public registry snapshot: US. Locale tags are intentionally omitted.