## Thinking Path > - Paperclip is the open source app people use to manage AI agents for work. > - The Advanced tab lets operators edit agent settings as YAML. > - Its first format embedded company catalogs, profile definitions, history, and instruction text. > - This made one agent document grow with unrelated company data. > - Removing those fields from the display also needs safe save behavior. > - This pull request renders a compact document and resolves sparse edits against saved state. > - Operators can change settings without copying shared data or deleting hidden values. ## Linked Issues or Issue Description Refs #2219. Follow-up to #18036. **Current behavior** The Advanced document expands shared profiles, embeds instruction files, and lists read-only state and unused connections. It also emits empty command lists and unset fields. **Proposed behavior** Show the agent's own settings and profile/instruction references. Omitted settings stay unchanged. Explicit empty values clear supported settings. A named instruction file changes only when supplied; `null` deletes that file. **Reason and benefit** An agent's YAML should remain readable when its company adds profiles or its instruction files grow. Every setting remains available through YAML or its owning settings tab. ## What Changed - Remove the read-only `observed` export and unused connection inventory. - Render profile-key references and instruction locations. Keep file contents and legacy prompt text out of the default editor. - Omit unset nullable fields, empty maps/lists, zero budget, standard permissions, and empty commands. - Add a sparse input schema and saved-state resolution. Preserve omitted fields, binding definitions, file contents, permissions, and channel settings. - Keep explicit clears and map/list replacement. Patch named instruction files and use `null` for deletion. Preserve hidden legacy prompt text unless explicitly changed. - Check profile references, shared edits, and file restrictions before writes. Keep revision guards, native authorization, and partial-save recovery. - Update documentation, verification maps, and regression coverage. Remove operating-system clipboard dependence from browser tests. ## Verification - All 48 jobs pass in the [final CI run](https://github.com/paperclipai/paperclip/actions/runs/40904124001) on `6dbb11d7a6`. Greptile is 5/5 on this exact commit. Both findings are resolved; there are no failed or pending checks. - Paperclip Review ended neutral because its agent finished without a complete assessment. It did not provide a code finding. Superagent Security Scan passed. - The focused suite passes 58 tests across YAML parsing, planning/saving, compact output, and the editor. - A large unit fixture with 30 profiles, 50 entries per profile, and a 1,000-line instruction file renders under 70 lines and is more than 95% smaller than the prior expanded representation. - All eight browser cases pass against real APIs and a dedicated PostgreSQL database. The compact-output case stays under 60 lines with large profiles and instruction text. It checks sparse saves and profile-key binding without changing shared definitions. The resource-save browser case also checks that unpinned skill shorthand does not trigger another sync during an unrelated save. - Browser coverage also checks resource saves/clears, secret redaction, key receipts through rename, stale drafts, lost responses, instruction relocation, and revision restore. The MCP fixture is a local target; no model run or external provider login is claimed. - Workspace build and typecheck pass. Map, Storybook catalog, and token gates pass. These checks and all eight browser cases passed after rebase onto current master, including its new Secrets regression. The merge conflict consisted of adjacent test additions; both were retained. The final skill no-op correction also passes a focused browser rerun. The mixed-resource channel regression failed before its fix and now passes, including revision restore with unpinned skills. UI typecheck passes after both corrections. - The first browser run hit a five-second test wait during an active multi-resource save. A focused rerun exposed shared clipboard interference. The helper now waits for save completion and uses scoped copy events plus keyboard input. The next full run passed. Earlier logs and screenshots remain outside the repository. Run the focused browser suite with: ```sh pnpm exec playwright test --config tests/e2e/playwright.config.ts tests/e2e/agent-configuration.spec.ts ``` ## Risks - Omitted fields now preserve saved values. Removing a line does not clear that setting. Supply its supported empty value instead. - Instruction file maps are patches. Old exports that removed a file by dropping its entry must now set that file to `null`. Entry files and read-only assets remain protected. - Explicit lists and adapter/runtime/metadata maps retain replacement behavior. Hidden legacy prompt text is preserved unless supplied explicitly; an empty string clears it. - Shared definition edits still require explicit consent. Saves still use sequential native APIs and can partially succeed. Existing unversioned resource race windows remain. - No database migration, new dependency, lockfile edit, or workflow change. ## Model Used OpenAI Codex, GPT-6 family. The exact serving model ID and context window are not exposed in this session. The work used reasoning, repository editing, code execution, and Playwright browser automation. ## Checklist - [x] I have included a thinking path that traces from project context to this change - [x] I have specified the model used (with version and capability details) - [x] I have checked ROADMAP.md and confirmed this PR does not duplicate planned core work - [x] I have searched GitHub for duplicate or related PRs and linked them above - [x] I have either (a) linked existing issues with `Fixes: #` / `Closes #` / `Refs #` OR (b) described the issue in-PR following the relevant issue template - [x] I have not referenced internal/instance-local Paperclip issues or links (only public GitHub `#NNN` / `github.com/paperclipai/paperclip` URLs) - [x] My branch name describes the change (e.g. `docs/...`, `fix/...`) and contains no internal Paperclip ticket id or instance-derived details - [x] I have run tests locally and they pass - [x] I have added or updated tests where applicable - [x] I have updated relevant documentation to reflect my changes - [x] I have considered and documented any risks above - [x] All Paperclip CI gates are green - [x] Greptile is 5/5 with no open P2s, recommendations, or follow-ups - [x] I will address all Greptile and reviewer comments before requesting merge --------- Co-authored-by: Paperclip <noreply@paperclip.ing>
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Hiring, configuration, and organization
Operators hire agents, configure their identity and instructions, assign reporting relationships, and manage their lifecycle. Built-in agents have their own setup and lifecycle constraints.
Feature ID: agents.
Implementation: hiring, configuration, organization.
Agent access: companion.
Sub-features
hire:agents/hire— choose identity, harness, model, and required account settings; edit reporting relationships through the agent configuration afterward.grok-bot:agents/grok-bot— experimental existing-Bot agent setup through remote OAuth, routine credentials, and an authenticated two-way challenge; current contact, stop and explicit recovery.instructions:agents/instructions— edit agent configuration and instruction files with durable revisions.organization:agents/organization— inspect and change reporting relationships through supported controls.primary-agent:agents/primary-agent— choose a personal primary agent for the company, confirm replacement, and inspect its roster/sidebar and task/chat defaults.lifecycle:agents/lifecycle— pause/resume or retire an agent while preserving history.built-in:agents/built-in— configure required agents without treating them as ordinary removable hires.api-keys:agents/api-keys— create and inspect named agent credentials, copy a new token once, and revoke it without changing agent identity.managed-agent-setup:agents/managed-agent-setup— probe, create, or adopt a qualified Anthropic managed-agent profile with pinned provider resources and retention acknowledgement.
How to get to it (user POV)
hire-agent
Use New agent from the roster or /agents/new.
Submitting the name creates an inactive record before adapter selection or account setup. A name-only draft returns to adapter selection when reopened. Save & exit keeps its configuration; Finish setup on the agent returns to the same record. Open an unfinished agent from the roster to reach its header. The header shows Finish setup instead of Run or Resume, including during computer preparation and verification. Terminating agents cannot reopen setup. Final submission requests approval when required, then follows the existing preparation and verification lifecycle.
Agent-owned plugin environments prepare the saved draft in the background when
their driver declares requiresAgent. The draft waits in verifying with its
setup hold until hiring finishes. Changing environments keeps the selected
account and Configure step, saves the selection, and invalidates its test.
Preparation and failed-save retries remain visible without reconnecting.
Companies requiring hire approval save the account with pending verification;
resource allocation waits for approval.
agent-configuration
Open /agents/:agentId and the configuration/instruction surfaces it exposes.
Open Advanced at /agents/:agentId/advanced for the compact agent
YAML configuration. Edit a name, budget,
runtime setting, and adapter key; save, reload, and check the ordinary settings
and Revisions. Try malformed YAML, an unknown field, omitted settings, a removed adapter key,
and a concurrent settings edit. Errors must retain the draft; stale saves return
a conflict. Unchanged secret markers must preserve their stored values. Navigating
away with a draft must show the existing unsaved-change guard. Reload saved
discards the draft. Also edit instruction text, skill pins, direct tool installs,
channel settings/resources, permissions/trust/project boundaries, secret operations,
and API key operations. Verify each result in its owning tab. Revision restore is
an isolated save. Default YAML excludes catalogs, inherited definitions, history, and instruction
contents. Verify profile-key references, named instruction-file patches (null
deletes one file), omitted-setting preservation, and explicit clears. Adding
unrelated company profiles must not grow this agent’s YAML. Inherited access and
history remain in their owning tabs. An
interrupted multi-resource save must report partial progress, preserve returned
one-time keys, and require reload before another save. Domain APIs retain their
existing authorization; a multi-resource save is not atomic.
For a low-trust agent, open Permissions / Trust → Allowed projects. An operator with agent-management permission can select additional projects and explicitly save them. Existing projects and other containment restrictions remain intact. Cancel discards the draft; a failed save retains it. Reload to verify persistence. This does not start or retry a task.
In /agents/all, select roster checkboxes and choose Edit connection & model.
A mixed selection offers one action per harness. Each field is opt-in. The editor
previews each changed value and excludes agents already at the target value.
Models must be compatible with every selected connection. Failed writes show
per-agent errors; Retry touches only the remaining agents. Connection pools and
externally managed agents are not editable through this shortcut.
Verify connection-only, model-only, both fields, mixed-harness selection, hidden selections, no-op counts, incompatible models, partial failure and retry. Reload the roster and compare stored settings, including unrelated heartbeat and adapter fields. A concurrent configuration edit must return a conflict. Shared runtime validation, access checks, revisions and audit logging still apply. Live runs retain their existing settings; model changes can reset saved sessions. Connection adoption can require an explicit reset of existing sessions.
organization
Use the roster’s organization view; /org redirects to the roster in the streamlined shell.
personal-primary-agent
Open an agent profile and choose Set as my primary. Inspect its crown on the profile/roster and its position in the Agents sidebar, then open a new task or Chat.
agent-api-keys
Open /agents/:agentId/api-keys → API Keys with an authenticated person who can manage agents. The operator CLI also supports paperclipai token agent create -C <company-id> --agent <agent-id> --name <label>, token agent list -C <company-id> --agent <agent-id>, and token agent revoke <key-id> -C <company-id> --agent <agent-id>.
managed-agent-cli
Use the operator command paperclipai managed-agent setup --company-id <company-id> --profile-key <key> --display-name <name> --api-key-secret-id <company-secret-id> --acknowledge-retention --json. Supply ANTHROPIC_API_KEY through the process environment. Use --agent-id, --agent-version, and --environment-id to adopt resources, or --probe for provider reads without profile persistence. The optional session-list cost ceiling is --max-session-list-cost-usd.
Driving it with Playwright and the Paperclip CLI
Preconditions: follow the baseline. Use a disposable company and supported adapter; hiring may require a formal approval.
hire-agent
Automated: new agent page and configuration form cover mocked UI behavior.
For an agent-owned plugin environment, verify preparation before connecting, same-agent probes, account preservation after an environment change, failed selection-save retry, and switching back while the computer stops. Confirm the setup hold still blocks ordinary work and API key creation before finishing. Start through the name/adapter dialog with a managed-only or forced Kubernetes policy and a draft that inherits its environment. Once preparation completes, confirm the auth choices, Advanced gateway, and saved subscription remain usable. The setup lifecycle tests exercise durable transitions with synthetic plugin resources; they do not prove live VM provisioning.
Manual: Hire an agent with a distinct name and role. Complete any required approval, reload the roster, and open its configuration. Confirm manager, adapter, and model persisted; run a small task to prove execution readiness.
For a new Codex hire, choose the Codex harness. Automatic selection uses Paperclip Runner on a qualified selected target; Advanced offers an explicit Legacy runner override. Record the persisted runner and underlying harness, rather than treating the displayed Codex name as execution proof. See runtime selection and validation and target qualification.
Repeat with an explicit Legacy Codex hire. If approval is required, compare its reviewed execution configuration before and after restart and activation; approval must retain the reviewed runner. Test an existing Legacy and native agent through an unrelated edit, reload and restart: neither is automatically upgraded.
Creation defaults also apply to API/CLI hires, built-ins, plugins and new team imports. Exports preserve resolved execution choices; a package without a runner choice uses the new-agent default, while updating an existing same-harness agent preserves its execution. For a native Codex import, edit a model or account binding and verify unchanged runtime settings survive; an explicit clear must stay cleared. Use the portability recipe for package preparation and boundaries.
For Claude Code on qualified macOS or GNU/Linux x64/ARM64, submit without a
runner override and inspect
saved configuration: paperclip_runner, provider: acpx, acpxAgent: claude,
and ordinary model claude-opus-5-5. The Advanced runner selector can explicitly
choose Legacy. Keep explicit model/account choices and saved runners on edits.
Verify useful output and a follow-up after a controller restart; setup success
alone does not establish session continuity. Unsupported architectures/libc and unknown environment qualification retain
Legacy. Darwin SSH also defaults to Legacy until automatic matching assets are
qualified; explicit matching native assets and saved native configurations remain
supported. Linux ARM64 cloud-image production remains deferred.
The current hiring wizard assigns the first hire CEO and subsequent hires General reporting to the CEO. Change manager/role afterward through supported configuration. Process/HTTP agents can be created through API/CLI but are excluded from the hiring picker; API fixture creation does not prove this UI journey.
agent-configuration
Automated: instruction service and instruction revisions cover file/revision contracts.
The AI account field regression checks duplicate provider names, account identity in choices and adoption confirmation, the exact selected grant, and disabled unavailable accounts with authorized metadata fixtures. Manually compare a personal API key and shared subscription with the same name in Harness / Runtime. Confirm their method, scope and available identity before saving. Reload the saved choice and verify the next eligible task uses it; labels alone do not establish credential validity or change account access.
Manual: Save a harmless instruction edit, reload, and verify its revision and effect in the next eligible run. Pause and resume the disposable agent; confirm pause prevents new work and does not erase previous runs.
For failed setup, use an unavailable model or invalid command on a disposable agent. Confirm the profile names the failed verification step and gives a relevant action. Check that it explains automatic retry and offers Retry now. Fix the configuration, retry, and reload; the failure must disappear only after readiness commits. Provider output and credentials must not appear in the lifecycle message.
An explicit runner change is a configuration change, with normal revisions and session invalidation. Obsolete Claude tuning options (including maxTurnsPerRun) are ignored with a field-specific warning; permission, network, filesystem and command incompatibilities still produce an error. Selecting another runner must not silently discard security settings or change an active run's recorded execution. Keep runner choice in Advanced and verify the next eligible run separately from historical transcripts.
Existing legacy Claude, Codex, and Grok Build agents on qualified default environments, or
probe-capable Daytona snapshots / immutable sandbox images, show Upgrade runner above their configuration. Verify a company owner with agents:configure and no instance-admin role can qualify the saved computer and upgrade. A caller without configuration permission must be denied before a probe starts. Exercise that action with
pending edits and an environment-variable draft. An unsaved change to a different
effective computer must disable the action and explain that the computer change
must be saved first; restoring the saved target must re-enable it. Reopen the page and compare the
saved harness, model, account bindings, instructions, and run policy. Check a
Grok upgrade with an unset or grok-build model: it must use grok-4.7.
Compare effective search policy before and after, including the implicit disabled
default and explicit enabled search. Verify task model and effort changes use the
Grok catalog and reach execution while retaining the account and search policy. Check a
saved maxTurnsPerRun: 1000: upgrade must warn and remove it. Test an initially
unqualified Daytona Paperclip Computer: click must probe, record qualification,
refresh availability, and only then save. A failed probe or changed selection must
leave the agent on Legacy. Check a rejected permission setting, repair it, and retry. Verify a real task before
and after migration, including its output, preserved history, and fresh session.
The notice must stay absent for native agents, other harnesses, and unsupported
targets. Discovery failure must not imply that an upgrade is available.
Navigate to another agent while an upgrade is pending. Its result must stay with
the original agent, without showing success on the new page or redirecting back.
Focused coverage: save receipt
and configuration form.
For an existing native agent on a Daytona snapshot or immutable sandbox image, use Test in its saved Harness or Runtime configuration after a managed computer update. This action qualifies the saved computer under the existing agent configuration permission before testing the runtime. A current proof must remain unchanged. A missing proof requires a real successful probe and verified cleanup. Failed qualification must stop the runtime test. Unsaved configuration or a different computer must not qualify a draft target. A company owner must not need instance-admin permission, and the generic environment probe must remain restricted. Existing runs retain their recorded allocation and snapshot binding.
Storybook: Runner upgrade mounts the production page and shell with mutable HTTP fixtures for both harnesses, pending, failure/retry, incompatible settings, repair, native/unsupported states, and mobile/light presentation. Fixture success does not establish real migration or provider execution.
organization
Automated: org chart is component evidence. Built-in setup also has configuration modal tests.
Manual: Inspect a manager and report, change the relationship through the offered controls, and reload both views. Exercise a rejected invalid relationship. Configure a built-in agent and verify it retains its required identity and restrictions.
personal-primary-agent
Automated: primary-agent context and primary-agent routes cover selection, company/user scope, and request contracts.
Manual: Select an available agent, reload, and inspect the retained personal choice. Replace it and verify confirmation is required. Leave or terminate the selected agent through permitted controls and inspect the unavailable/cleared state. Switch company/user to check isolation. Open a task and Chat with a valid draft or recent selection; verify those explicit choices take precedence over the primary fallback. Opening Chat must not start execution.
agent-api-keys
Automated: CLI token tests mock create/list/revoke. Cross-tenant routes, agent permissions, and authentication middleware cover company/key ownership, management permission, responsible-user binding, and denial. They do not prove a browser-created key working against a live instance.
Manual: As an authenticated person with agents:create, create a named key for an eligible disposable agent and copy it privately from the once-only display. Make a harmless same-company agent request with that bearer, then reload the Keys tab and verify only metadata remains. Revoke the key through UI or CLI, reload, and retry the exact same bearer: authentication must fail. Inspect key-created/key-revoked activity without token values. Test a board person lacking agent-management permission, an agent caller, another company’s agent, a different agent’s key ID, and a pending-approval/terminated target. A created key without a real responsible-user binding is a failed acceptance prerequisite, not a working credential.
Sources: Keys tab, key routes, key service, authentication, and CLI token commands.
managed-agent-cli
Automated: Managed-agent CLI uses mocked provider/API responses. Profile route authorization and remote profiles cover actor/company checks and qualification. They do not establish provider provisioning or a useful managed task.
Manual: Start with known adopted provider IDs in an authorized disposable provider account. Run --probe and verify only provider reads: no resources are created and no Paperclip profile is written. Reject unsafe tools/network/package configuration, an unsupported model, duplicate profile matches, a missing retention acknowledgement, and a malformed secret UUID. During persistence, reject missing, inactive, or foreign-company secret references. Then create or adopt a locked profile in a disposable company; inspect its pinned version, model, environment, retention attestation, and cost ceiling through the profile API. Repeat setup and verify resource reuse. Reject viewer/agent writes and foreign-company references. Qualify useful task execution separately through the runtime recipe; a successful probe is not execution acceptance.
Sources: Managed-agent CLI, profile routes, profile service, and runtime validation.
Gotchas
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Managed-agent probing is read-only at the provider and does not persist a Paperclip profile. The explicit retention acknowledgement remains required even for probe.
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Agent keys, human CLI tokens, and personal assistant OAuth grants are different credentials. Never include a key’s plaintext token in screenshots, logs, or verification artifacts.
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A roster entry is not proof of an authenticated or invokable adapter.
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Pending hires may live in approval/task surfaces rather than the active roster.
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Skill and tool grants are separate: see skills and app permissions.
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A personal primary agent is a per-user/company preference. It does not change reporting lines, stars, permissions, or another person's primary agent.
connect-grok-bot
Choose Invite an external agent → Grok Bot, identify the Bot by its desktop name, connect its remote MCP plugin, configure a webhook-only routine, and verify delivery plus authenticated reply. Save & exit resumes the same agent. Keep pairing codes in browser authorization and routine credentials in Paperclip’s fields. A working Bot web URL is not required.
Prerequisites: authenticated public HTTPS, Assistant connections (MCP), Paperclip Runner and Grok Bot experimental settings. Cloud uses its normal managed Runner environment. Provider usage is unknown. Routine uncertainty blocks new assignments until explicit inspection and recovery; stopping work revokes Paperclip authority without confirming remote termination.
Evidence: source implementation and focused protocol tests; real provider assigned/proactive workflows and deployed managed acceptance remain release gates.
Documentation scope: Agents, organization, and runtime setup
Per-harness/model/account capabilities, every instruction-file error, and complete built-in-agent lifecycle variants remain separate qualification matrices.