<!-- entire-trail-link-start --> https://entire.com/gh/paperclipai/-/trails/175/changes/paperclip/175 <!-- entire-trail-link-end --> ## Thinking Path > - Paperclip is the open source app people use to manage AI agents for work. > - Operators configure each agent through several settings tabs. > - Operators also need one complete, editable configuration document. > - The document must retain each resource service's access and validation rules. > - This pull request defines the `paperclip/v1` Agent YAML format and adds an Advanced editor. > - The editor previews changes, rejects stale core writes, and explains partial saves. > - Operators can edit agent settings in one place and verify the saved state after reload. ## Linked Issues or Issue Description Refs #2219. Related settings work: #10974. **Problem or motivation** Agent configuration spans profile, runtime, instructions, skills, tools, channels, permissions, secrets, keys, and revision history. Operators cannot inspect and edit those settings as one versioned YAML document. **Proposed solution** Add an Advanced agent tab with a YAML editor. Define a shared document schema. Read and write resources through their existing APIs. Separate editable settings, explicit commands, and read-only observed state. **Alternatives considered** A raw agent-row editor would omit related resources. A generic database update would bypass resource ownership. The editor therefore uses the existing resource contracts and records partial results when a later request fails. **Roadmap alignment** This extends the shipped agent configuration capability. It relates to easy AGENTS.md configuration, multi-harness teams, governed tool access, and secrets management. Stored credentials remain redacted. This format is an editable settings view; it does not add company portability or provider consent. ## What Changed - Add the `paperclip/v1` Agent document schema and format documentation. - Add the Advanced route, sidebar entry, YAML editor, validation, change summary, save progress, and reload recovery. - Cover core settings, instruction files, skill pins, tool installs/profiles/policies, channels, permissions, secret operations, API keys, and revision restore. - Add private-keyed configuration revisions checked under the agent write lock. Read the current key through its owner so file-based rotation does not require restarting the server. Preserve unchanged secret markers at their original paths. - Retain drafts and returned credentials after partial saves. Require reload before retrying commands. Prevent duplicate submissions. Keep new key tokens visible through rename and disable saves with an empty change plan. - Send only changed channel settings. Require explicit intent for shared profile edits. Load destination instruction files when changing their location. - Update Storybook fixtures, verification maps, and regression tests. Add browser acceptance through real APIs and PostgreSQL. ## Verification - `pnpm -r typecheck` passes. - `pnpm build` passes. - The focused UI suite passes all 50 tests. The API/revision helper suites pass all 93 tests. - All 65 lifecycle tests pass with a dedicated PostgreSQL database. They exercise real row locks, redaction, revision history, audit, and company access. - All six browser acceptance cases pass. They check saved settings and clears, secret redaction, key creation/revocation, stale drafts, lost-response recovery, instruction relocation, revision restore, and key-token retention through rename. The tests use real resource APIs and storage. The MCP target uses the existing local provider fixture. No model run or provider login is claimed. - Signing-key regressions cover both environment changes and real in-place key-file rotation. The protected database save/fencing cases pass after removing the cache. A local measurement of 1,000 file-backed revision calculations took 48 ms. - `pnpm check:token-gates`, `node scripts/check-maps.mjs`, and Storybook catalog checks pass. - The full [PR CI run](https://github.com/paperclipai/paperclip/actions/runs/40725425470) passes on `34ed97bbf9`: all 48 jobs, including all eight browser shards. Greptile is 5/5 on this commit, with no unresolved review threads. This final commit refreshes CI after a runner-routing fallback; its source tree matches `fb4cf488cf`. - Paperclip Review and Superagent Security Scan ended neutral because their external agents did not complete a valid assessment/receipt. Superagent passed on `fb4cf488cf`, which has the identical source tree. One request to retry the final scan returned HTTP 404. Neither check reports a code finding. - The local full-suite attempt was blocked by host System V semaphore exhaustion. Acceptance and lifecycle verification used an isolated PostgreSQL 18 container. Earlier CI runners were interrupted. A local combined run hit hook/test timeouts; the full 88-test route file passed after the builds finished. The final full CI run passes. Earlier failure logs and browser traces remain retained outside the repository. To run the browser regression: ```sh pnpm exec playwright test --config tests/e2e/playwright.config.ts tests/e2e/agent-configuration.spec.ts ``` ## Risks - Multi-resource saves are sequential. Earlier operations can remain saved if a later operation fails. The editor reports the completed steps and requires reload. - Core settings and managed instruction files have atomic revision/hash checks. Other unversioned resource writes and external supporting files retain a race window after preflight. - Shared profile definitions affect other bindings. The editor requires `updateSharedDefinition: true` for those edits. - The editor follows native service normalization and experimental settings. Canonical reload can add generated access profiles or mask environment values. - New editor dependencies require the repository's normal automated lockfile update. This pull request does not edit the lockfile or add a database migration. ## Model Used OpenAI Codex, GPT-6 family. The exact current model version was not exposed. The work used reasoning, repository tools, code execution, and browser automation. Earlier work in this chat used the configured Codex model before a model switch; its exact model ID and context window were not exposed. The current context window size is also not exposed. ## 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. 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 complete agent
YAML configuration. Edit a name, budget,
runtime setting, and adapter key; save, reload, and check the ordinary settings
and Revisions. Try malformed YAML, a missing/unknown field, a removed nested 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. Inherited access/history under observed is read-only. 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.