Agent skill

Pp Unipile

by mvanhorn in mvanhorn/printing-press-library

Every Unipile endpoint as a typed command, plus a local mirror that makes cross-provider search possible and an invitation ledger that shows how much LinkedIn headroom you have left.

Apache-2.0Auto-check: notesProductivity & Automation

Install Pp Unipile

skills CLI
$ npx skills add mvanhorn/printing-press-library --skill pp-unipile -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install mvanhorn/printing-press-library pp-unipile --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/mvanhorn/printing-press-library.git skills-src && mkdir -p .claude/skills && cp -r skills-src/cli-skills/pp-unipile .claude/skills/pp-unipile && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
pp-unipile
GitHub stars
2.1k
Token cost
~8.9k tokens
SKILL.md length
3,912 words
Files
1
Skills in repo
506
Repo updated
First seen
Licence
Apache-2.0

At a glance

Every Unipile endpoint as a typed command, plus a local mirror that makes cross-provider search possible and an invitation ledger that shows how much LinkedIn headroom you have left.

  • Works in 6 steps: recall before any discovery → decision tree → always read warnings → …
  • Phrases: check my unified inbox
  • SKILL.md covers Prerequisites: Install the CLI, When to Use This CLI, Anti-triggers and Unique Capabilities, plus 6 more sections
  • Calls go, claude and npx; needs UNIPILE_API_KEY

What it does

Pp Unipile is an agent skill from mvanhorn/printing-press-library. Every Unipile endpoint as a typed command, plus a local mirror that makes cross-provider search possible and an invitation ledger that shows how much LinkedIn headroom you have left. Trigger phrases: check my unified inbox, who accepted my LinkedIn invitations, how many invitations can I still send today, find conversations nobody replied to, search my messages across providers, use unipile, run unipile.

Its SKILL.md is about 8.9k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Productivity & Automation, covering Email management. It works with LinkedIn. The repository describes itself as: Official library of CLIs generated by the CLI Printing Press. Endorsed, tested, and community-contributed. The licence is Apache-2.0.

When your agent uses it

  • Phrases: check my unified inbox
  • Who accepted my LinkedIn invitations
  • How many invitations can I still send today
  • Find conversations nobody replied to

Example prompts

  • “/pp-unipile”

Requirements

  • Node.js
  • Pre-approved tools (allowed-tools): Read, Bash

Workflow steps

6 steps, taken from the step headings in SKILL.md.

  1. recall before any discovery
  2. decision tree
  3. always read warnings
  4. teach & after finalizing your response - always
  5. playbooks - optional flags, automatic synthesis
  6. playbook amend & when your debug response identifies a correction

What it can do on your machine

Read from SKILL.md and the folder at commit d9a1696. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Bash

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • go
    • claude
    • npx

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use npx, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • UNIPILE_API_KEY

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Pp Unipile loads about 8.9k tokens when it runs. Until then it costs about 108 tokens; SKILL.md has 3,912 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~108
When it runs · the whole SKILL.md, loaded when a task matches
~8.9k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
    allowed-tools: Read, Bash

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from mvanhorn/printing-press-library at commit d9a1696, republished under its Apache-2.0 licence (© mvanhorn). 3,912 words, ~8,932 tokens.

Download SKILL.mdSave it as .claude/skills/pp-unipile/SKILL.md (or your agent's skills folder).
name
pp-unipile
description
Every Unipile endpoint as a typed command, plus a local mirror that makes cross-provider search possible and an invitation ledger that shows how much LinkedIn headroom you have left. Trigger phrases: `check my unified inbox`, `who accepted my LinkedIn invitations`, `how many invitations can I still send today`, `find conversations nobody replied to`, `search my messages across providers`, `use unipile`, `run unipile`.
allowed-tools
Read, Bash
author
fuushyn
license
Apache-2.0
argument-hint
<command> [args] | install cli|mcp
<!-- GENERATED FILE — DO NOT EDIT.
     This file is a verbatim mirror of library/social-and-messaging/unipile/SKILL.md,
     regenerated post-merge by tools/generate-skills/. Hand-edits here are
     silently overwritten on the next regen. Edit the library/ source instead.
     See the repository agent guide, section "Generated artifacts: registry.json, cli-skills/". -->

Unipile — Printing Press CLI

Prerequisites: Install the CLI

This skill drives the unipile-pp-cli binary. You must verify the CLI is installed before invoking any command from this skill. If it is missing, install it first:

  1. Install via the Printing Press installer. It defaults binaries to $HOME/.local/bin on macOS/Linux and %LOCALAPPDATA%\Programs\PrintingPress\bin on Windows:
    bash
    npx -y @mvanhorn/printing-press-library install unipile --cli-only
  2. Verify: unipile-pp-cli --version
  3. Ensure the reported install directory is on $PATH for the agent/runtime that will invoke this skill.

If the npx install fails (no Node, offline, etc.), fall back to a direct Go install (requires Go 1.26.6 or newer). This installs into $GOPATH/bin (default $HOME/go/bin), so add that directory to $PATH instead:

bash
go install github.com/mvanhorn/printing-press-library/library/social-and-messaging/unipile/cmd/unipile-pp-cli@latest

If --version reports "command not found" after install, the runtime cannot see the binary directory on $PATH. Do not proceed with skill commands until verification succeeds.

Unipile unified LinkedIn, WhatsApp, Telegram, Instagram, Messenger, X, Gmail, Outlook, IMAP, and calendars into one API, then stopped at the API. This is the missing operator layer: the full endpoint surface as shell-native commands with structured errors and cursor auto-pagination, a local SQLite mirror that answers cross-provider questions no single call can, and a budget command that counts invitations already sent against the caps LinkedIn enforces but Unipile does not.

When to Use This CLI

Reach for this CLI when a task touches messages, email, calendars, or LinkedIn activity across more than one provider, or when the answer requires history rather than a single live call. It is the right tool for triaging a unified inbox, building follow-up lists from prior conversations, measuring outreach conversion, and staying under LinkedIn's rate caps. It is also the fastest path to any single Unipile endpoint from a shell or a script.

Anti-triggers

Do not use this CLI for:

  • Do not use this CLI for Unipile API v2; this targets v1 and v2 tenants use a different DSN and endpoint surface.
  • Do not use this CLI to connect a brand new provider account interactively; the hosted auth wizard in the Unipile dashboard is the supported path for first-time OAuth and QR flows.
  • Do not use this CLI as a webhook receiver; it can register webhooks but your own server must accept the callbacks.
  • Do not use this CLI to bulk-send invitations beyond what 'budget' reports as remaining; exceeding LinkedIn's caps risks restricting the underlying account.

Unique Capabilities

These capabilities aren't available in any other tool for this API.

Account safety
  • budget — See how many LinkedIn invitations you have left today and this week, counted from your synced invitation history.

    Check this before any bulk invitation run so you do not get the underlying LinkedIn account restricted.

    bash
    unipile-pp-cli budget --agent
Local state that compounds
  • search — Full-text search every message, email, attendee, and relation across all connected providers at once, offline.

    Use this instead of N per-provider list calls when you need to find where something was said.

    bash
    unipile-pp-cli search "pricing" --agent --limit 20
  • digest — What changed across every connected provider since the last sync.

    Run this after sync to get a single catch-up summary instead of polling nine surfaces.

    bash
    unipile-pp-cli digest --agent
Cross-provider views
  • contact — Everything the local mirror knows about one person: connection state, invitation history, and every conversation with per-direction message counts.

    Reach for this before writing to someone, so the message is informed by every prior touch across every provider.

    bash
    unipile-pp-cli contact "Lakshya" --agent
  • inbox — One table of everything unread across LinkedIn, WhatsApp, Telegram, Instagram, Messenger, and email.

    This is the daily triage view; use it to decide what to answer before opening any provider UI.

    bash
    unipile-pp-cli inbox --agent --limit 25
  • thread — Read one conversation end to end with attendee IDs resolved to real names.

    Use this when you need the full context of a conversation in one readable payload.

    bash
    unipile-pp-cli thread --chat example-chat-id --agent
Outreach loop
  • silent — Find conversations where you sent the last message and got no reply for N days.

    Use this to build a follow-up list without re-reading every thread.

    bash
    unipile-pp-cli silent --days 7 --agent
  • accepted — New LinkedIn connections since your last sync that you have not messaged yet.

    This is the highest-conversion follow-up queue in outreach; use it right after a sync.

    bash
    unipile-pp-cli accepted --since 7d --agent
  • funnel — Sent, accepted, and replied counts with conversion rates over a time window.

    Use this to judge whether outreach copy is working before scaling send volume.

    bash
    unipile-pp-cli funnel --weeks 4 --agent
  • engagement — Who reacted to or commented on your posts, flagged by whether they are already a connection.

    Use this to turn warm post engagement into a targeted invitation list.

    bash
    unipile-pp-cli engagement --agent --limit 20

Command Reference

accounts — Accounts management

  • unipile-pp-cli accounts connect — Link to Uniple an account of the given type and provider.
  • unipile-pp-cli accounts delete — Unlink the given account to Unipile.
  • unipile-pp-cli accounts get — Retrieve the details of an account.
  • unipile-pp-cli accounts list — Returns a list of the accounts linked to Unipile.
  • unipile-pp-cli accounts reconnect — Reconnect an account previously linked to Unipile that has been disconnected.
  • unipile-pp-cli accounts resend-checkpoint — Might it be 2FA, OTP or In-app Validation, this route makes you able on certain providers to resend the notification.
  • unipile-pp-cli accounts solve-checkpoint — Allows you to provide a code which will solve a checkpoint encountered during a native authentication.
  • unipile-pp-cli accounts update — Update the proxy configuration of an existing account.

calendars — Calendars management

  • unipile-pp-cli calendars get — Retrieve the details of a calendar.
  • unipile-pp-cli calendars list — Returns a list of calendars.

chat-attendees — Manage chat attendees

  • unipile-pp-cli chat-attendees get — The id of the wanted attendee.
  • unipile-pp-cli chat-attendees list — Returns a list of messaging attendees. Some optional parameters are available to filter the results.

chats — Manage chats

  • unipile-pp-cli chats delete — Delete a chat. Supported for WhatsApp and LinkedIn only.
  • unipile-pp-cli chats get — Retrieve the details of a chat.
  • unipile-pp-cli chats list — Returns a list of chats. Some optional parameters are available to filter the results.
  • unipile-pp-cli chats start — Start a new conversation with one or more attendee.
  • unipile-pp-cli chats update — Perform an action like changing the read status, muting the chat, retrieving a group invite link, etc.

drafts — Manage drafts

  • unipile-pp-cli drafts — ⚠️ Interactive documentation does not work on this route (child parameters not correctly applied in snippet)

emails — Emails management

  • unipile-pp-cli emails delete — Delete an email by moving it to the Trash folder.
  • unipile-pp-cli emails get — Retrieve the details of an email.
  • unipile-pp-cli emails list — Returns a list of emails.
  • unipile-pp-cli emails list-contacts — Returns a list of contacts from the email provider. Supported for Gmail (Google OAuth) and Microsoft (Outlook) only.
  • unipile-pp-cli emails send — ⚠️ Interactive documentation does not work on this route (child parameters not correctly applied in snippet)
  • unipile-pp-cli emails update — Update an email.

folders — Manage folders

  • unipile-pp-cli folders get — Retrieve the details of a mail folder.
  • unipile-pp-cli folders list — Returns a list of all email folders.

hosted — Manage hosted

  • unipile-pp-cli hosted — Create a url which redirect to Unipile's hosted authentication to connect or reconnect an account.

linkedin — Manage linkedin

  • unipile-pp-cli linkedin action-user — Add a candidate to a Recruiter pipeline, save a Sales Navigator lead, etc.
  • unipile-pp-cli linkedin close-jobs — Close a job offer you have posted.
  • unipile-pp-cli linkedin company — Get a company profile from its name or ID.
  • unipile-pp-cli linkedin create-jobs — Create a new job offer draft.
  • unipile-pp-cli linkedin endorse-profile — This route can be used to endorse a skill of a user profile.
  • unipile-pp-cli linkedin get-applicants — Retrieve the details of a user that has applied to a given offer. Applies to Classic job posting only.
  • unipile-pp-cli linkedin get-jobs — Retrieve a job offer.
  • unipile-pp-cli linkedin get-projects — Retrieve Recruiter hiring project from ID
  • unipile-pp-cli linkedin inmail-balance — Get balance for subscribed premium features.
  • unipile-pp-cli linkedin list-applicants — Retrieve all the users that have applied to a given offer.
  • unipile-pp-cli linkedin list-contracts — Returns a list of your LinkedIn available contracts
  • unipile-pp-cli linkedin list-jobs — Retrieve the job offers you have posted on LinkedIn whether they are open, closed or still drafts.
  • unipile-pp-cli linkedin list-projects — Retrieve list of LinkedIn Recruiter hiring projects.
  • unipile-pp-cli linkedin parameters-search — LinkedIn doesn't accept raw text as search parameters, but IDs.
  • unipile-pp-cli linkedin publish-jobs — Publish the job posting draft you have been working on.
  • unipile-pp-cli linkedin raw — This magic route is intended for advanced users who wish to use LinkedIn's features beyond our current capabilities.
  • unipile-pp-cli linkedin resume-applicants — This route can be used to download the resume of a job applicant.
  • unipile-pp-cli linkedin search — Search people and companies from the Linkedin Classic as well as Sales Navigator APIs.
  • unipile-pp-cli linkedin select-contracts — Select a Recruiter or Sales navigator contract to be used on your account
  • unipile-pp-cli linkedin solve-checkpoint-jobs — Solve a checkpoint to verify your member privilegies.
  • unipile-pp-cli linkedin update-jobs — Edit an existing job posting.

messages — Manage messages

  • unipile-pp-cli messages delete — Delete a message. Supported for WhatsApp and LinkedIn only.
  • unipile-pp-cli messages get — Retrieve the details of a message.
  • unipile-pp-cli messages list — Returns a list of messages. Some optional parameters are available to filter the results.
  • unipile-pp-cli messages update — Edit a message. Supported for WhatsApp and LinkedIn Classic only.

posts — Posts features

  • unipile-pp-cli posts create — Publish a post.
  • unipile-pp-cli posts get — Retrieve the details of a post.
  • unipile-pp-cli posts react — React to either a post or a post comment.

users — Users features

  • unipile-pp-cli users cancel-sent — Cancel a pending invitation sent to someone.
  • unipile-pp-cli users edit-me — Modify informations on account owner profile.
  • unipile-pp-cli users followers — Returns a list of all the followers of the current user.
  • unipile-pp-cli users following — Returns a list of all the followed accounts of an account.
  • unipile-pp-cli users get — Retrieve the profile of a user.
  • unipile-pp-cli users invite — Send an invitation to add someone to your contacts.
  • unipile-pp-cli users list-received — Returns a list of all invitations that have been received.
  • unipile-pp-cli users list-sent — Returns a list of all invitations sent that are pending.
  • unipile-pp-cli users me — Retrieve informations about account owner.
  • unipile-pp-cli users relations — Returns a list of all the relations of an account.
  • unipile-pp-cli users respond-received — Accept or decline a connection invitation.

webhooks — Webhooks management

  • unipile-pp-cli webhooks create — Create a webhook.
  • unipile-pp-cli webhooks delete — Delete a webhook.
  • unipile-pp-cli webhooks list — Returns a list of the webhooks.
Finding the right command

When you know what you want to do but not which command does it, ask the CLI directly:

bash
unipile-pp-cli which "<capability in your own words>"

which resolves a natural-language capability query to the best matching command from this CLI's curated feature index. Exit code 0 means at least one match; exit code 2 means no confident match — fall back to --help or use a narrower query.

Recipes

Daily triage
bash
unipile-pp-cli inbox --agent --select items.provider,items.name,items.last_message,items.timestamp

Returns only the four fields needed to decide what to answer, instead of the full chat payload for every unread conversation.

Follow-up queue
bash
unipile-pp-cli silent --days 5 --agent

Lists conversations where you spoke last and nobody replied, which is the list worth acting on today.

Safe outreach check
bash
unipile-pp-cli budget --agent

Reports remaining daily and weekly LinkedIn invitation and profile-view headroom before a send run starts.

Warm connection targets
bash
unipile-pp-cli engagement --agent --limit 20

Shows who engaged with your posts and is not yet a connection, which converts far better than cold invitations.

Find where something was said
bash
unipile-pp-cli search "contract" --agent --limit 15

Searches messages and emails across every provider from the local mirror, with no API call and no per-provider loop.

Auth Setup

Unipile authenticates with an Access Token sent as the X-API-KEY header, and every customer gets their own DSN base URL. Set UNIPILE_API_KEY to your token and UNIPILE_BASE_URL to your DSN from the Unipile dashboard. If your environment blocks custom ports, Unipile also accepts the port as a query parameter on standard 443.

Run unipile-pp-cli doctor to verify setup.

Agent Mode

Add --agent to any command. Expands to: --json --compact --no-input --no-color.

  • Pipeable — JSON on stdout, errors on stderr

  • Filterable — --select keeps a subset of fields. Dotted paths descend into nested structures; arrays traverse element-wise. Critical for keeping context small on verbose APIs:

    bash
    unipile-pp-cli accounts list --agent --select connection_params,created_at,current_signature
  • Previewable — --dry-run shows the request without sending

  • Offline-friendly — sync/search commands can use the local SQLite store when available

  • Non-interactive — never prompts, every input is a flag

  • Explicit confirmation — --agent does not imply --yes; pass --yes separately only after the target, arguments, and side effects are clear

  • Explicit retries — use --idempotent only when an already-existing create should count as success, and use --ignore-missing only when a missing delete target should count as success

Response envelope

Commands that read from the local store or the API wrap output in a provenance envelope:

json
{
  "meta": {"source": "live" | "local", "synced_at": "...", "reason": "..."},
  "results": <data>
}

Parse .results for data and .meta.source to know whether it's live or local. A human-readable N results (live) summary is printed to stderr only when stdout is a terminal AND no machine-format flag (--json, --csv, --compact, --quiet, --plain, --select) is set — piped/agent consumers and explicit-format runs get pure JSON on stdout.

Paths and state

Agents should treat the CLI's path resolver as part of the runtime contract:

  • Use --home <dir> for one invocation, or set UNIPILE_HOME=<dir> to relocate all four path kinds under one root.

  • Use per-kind env vars only when a specific kind must diverge: UNIPILE_CONFIG_DIR, UNIPILE_DATA_DIR, UNIPILE_STATE_DIR, UNIPILE_CACHE_DIR.

  • Resolution order is per-kind env var, --home, UNIPILE_HOME, XDG (XDG_CONFIG_HOME, XDG_DATA_HOME, XDG_STATE_HOME, XDG_CACHE_HOME), then platform defaults.

  • config contains settings like config.toml and profiles. data contains credentials.toml, data.db, cookies, and auth sidecars. state contains persisted queries, jobs, and teach.log. cache contains regenerable HTTP/cache files.

  • Stored secrets live in credentials.toml under the data dir. Existing legacy config.toml secrets are read for compatibility and leave config.toml on the first auth write.

  • Run unipile-pp-cli doctor --fail-on warn to surface path and credential-location warnings. agent-context exposes a schema v4 paths block for agents that need the resolved dirs.

  • For MCP, pass relocation through the MCP host config. The MCP binary does not inherit CLI flags:

    json
    {
      "mcpServers": {
        "unipile": {
          "command": "unipile-pp-mcp",
          "env": {
            "UNIPILE_HOME": "/srv/unipile"
          }
        }
      }
    }

Fleet precedence: an inherited per-kind env var overrides an explicit --home for that kind. Use UNIPILE_HOME or per-kind vars as durable fleet levers, and use --home only for a single invocation. Relocation is not reversible by unsetting env vars; move files manually before clearing UNIPILE_HOME, or doctor will not find credentials left under the former root.

Automatic learning

This CLI ships a self-capturing learning loop. The CLI does its own bookkeeping: every invocation is journaled locally, a failed flag followed by a corrected retry auto-derives a flag_alias candidate, and a teach on a query family without a playbook auto-synthesizes a playbook_candidate from the session's journal. Your job is judgment only: recall first, act on surfaced candidates, teach the final answer, playbook amend when you observe a correction. You never record failures by hand.

Show full SKILL.md (1,609 more words)Show less
Step 1: recall before any discovery

Before list/search/drill commands on a new user question, run:

bash
unipile-pp-cli recall "<user's question>" --agent

The response envelope:

json
{
  "query": "...",
  "normalized": "<normalized form>",
  "query_entities": ["..."],
  "found": true | false,
  "match_score": 0.0,
  "results": [
    { "resource_id": "...", "resource_type": "...", "venue": "...",
      "confidence": 2, "entity_match": "exact|partial|unknown",
      "source": "taught|preseed|pattern", "warnings": ["..."] }
  ],
  "mismatches": [ /* only when --debug-mismatches */ ],
  "warnings": [ /* top-level */ ],
  "candidates": [
    { "id": 12, "class": "flag_alias | playbook_candidate",
      "summary": "...", "sightings": 3, "last_seen": "...",
      "rationale": "...",
      "next_action": ["<trial command>", "unipile-pp-cli learnings confirm 12"] }
  ],
  "playbook": {
    "query_family": "...",
    "playbook": {
      "steps": [ { "cmd": "<command with {slot} substitution>", "purpose": "..." } ],
      "entity_slots": ["$ENTITY"],
      "expected_tool_calls": 3
    },
    "slots_resolved": { "$ENTITY": { "token": "<live token>", "canonical": "<canonical>" } },
    "notes": "<workarounds + gotchas for this query family>"
  },
  "notes": "<duplicate surface for non-playbook callers>"
}

Empty-store short-circuit: if the store has no learnings, playbooks, or candidates yet (recall finds nothing and learnings list and learnings candidates are both empty), skip recall for the rest of this session instead of taxing every query; resume recall-first once something has been taught.

Step 2: decision tree

Read candidates, playbook, notes, results[0], and warnings in that order:

if Candidates present (warnings include "candidates_present"):
    -> candidates are try-then-confirm, never facts. Follow each candidate's
       two-step next_action verbatim: run the trial command first, then run
       `learnings confirm <id>` only after the trial verified the behavior.
       Reject a wrong candidate with `learnings reject <id>`.
    -> NEVER re-teach something recall surfaced as a candidate; confirm or
       reject that candidate instead of teaching a duplicate.
    -> candidates ride alongside playbooks and resource hits, not instead of
       them; continue with the branches below after acting on them.

if Playbook present:
    -> READ Playbook.notes verbatim FIRST (workarounds + gotchas the CLI surface doesn't expose)
    -> replay Playbook.steps in order, substituting Playbook.slots_resolved entries
       for the entity slot tokens. If a step's slot is unresolved, fall back to
       discovery for that step only.
    -> the Playbook's expected_tool_calls is a budget; if you find yourself running
       materially more, record the divergence via `unipile-pp-cli playbook amend`
       at end-of-session.

elif Notes present (no Playbook):
    -> read Notes verbatim before any discovery step; they carry known gotchas
       for this query family even when no structured choreography exists yet.

elif Found AND Results[0].EntityMatch == "exact" AND Results[0].Confidence >= 2:
    -> skip discovery; fetch live data for Results[*].ResourceID in parallel

elif Found AND Results[0].EntityMatch == "partial":
    -> candidate hint, NOT a hit; read the resource title to validate before trusting

elif (any row in Mismatches[] when --debug-mismatches was passed):
    -> treat as cold start; the stored learning is for a different entity
       (different canonical resolved from query_entities)

else:  // Found == false, no playbook, no notes
    -> cold start; run discovery normally; teach the answer afterward (Step 4).
       If the family has no playbook yet, that teach auto-synthesizes a
       playbook candidate from this session's journal - you do not need to
       record one by hand.

Playbook and Notes are orthogonal to the per-resource path. A recall response can carry both a Playbook AND a Results[] hit - use both: the Playbook tells you which choreography to run; the resource hits short-circuit specific steps. Default to skipping mismatches; pass --debug-mismatches only when investigating cold-start surprises.

Candidate judgment details: learnings confirm <id> prints the candidate's full payload before materializing it - check that the printed payload matches the behavior you verified. learnings reject <id> tombstones the derivation signature so the same candidate does not resurface. The envelope carries only the few candidates worth acting on now; unipile-pp-cli learnings candidates lists the full open set.

Graceful degradation: if learnings confirm is an unknown command, you are driving an older binary - ignore the candidates guidance and follow the rest of the protocol.

Step 3: always read warnings
  • low_confidence: row exists at confidence<2. Treat as a hint, not a skip-discovery hit.
  • resource_not_in_store: the local store doesn't have the resource the learning points at. The match validator couldn't classify entities — direct-fetch and re-evaluate.
  • cross_alias_match (per-result): the row was taught under a different alias and matched the live query's canonical via entity_lookups (e.g., a "USA" teach satisfying a "United States" recall). Trust the resource_id.
  • similar_shape_different_entity:<canonical> (top-level): a structurally matching row exists but its canonical entity differs from the live query's. Treated as cold start; the warning carries the conflicting canonical as a hint, but the row is NOT promoted into Results.
  • ambiguous_alias (top-level): a single query entity resolved to multiple canonicals (e.g., "Cards" → Arizona Cardinals + St. Louis Cardinals). Surface the ambiguity from context before committing to a resource.
  • candidates_present (top-level): the envelope carries a candidates section. Handle it via the candidates branch in Step 2 before anything else.
  • lookup_refresh_available (top-level): an entity in the query has no lookup row yet, but synced data could provide one. Run unipile-pp-cli sync to refresh entity lookups.
  • Top-level no_learnings_for_query_family: the table had no rows above the Jaccard floor. Pure cold start.
Step 4: teach & after finalizing your response - always

Teaching is unconditional. After resolving a query the store could not answer, background-teach the final resource mapping - no call-count threshold, no judging whether it was "worth" learning. The teach is the anchor of the loop: it triggers playbook synthesis for a family without a playbook, and same-referent phrasings fold into one family so near-duplicate teaches do not fragment the store. Fire it after assembling your user-facing response but BEFORE emitting it, with a shell & so the call returns immediately:

bash
unipile-pp-cli teach --query "<user's question>" --resource-type <type> --resource <id1> --resource <id2>
# (append shell `&` to background it)

Silent on success. Errors only land in teach.log under the resolved state dir. Teach the most specific resource - if the user asked a broad question and you walked through parent records to find the specific answer, teach the leaf id, not the parent. The CLI uses seeded entity_lookups for cross-alias resolution at recall time, so a teach under one alias (e.g., "Niners") satisfies future queries under another alias (e.g., "49ers", "San Francisco") automatically.

PII rule: teach the structural question with identifiers stripped - never include names, emails, phone numbers, account ids, or other personal identifiers in taught queries or notes. The CLI scans teach queries for obvious email/phone shapes and warns, but does not block; strip before teaching rather than relying on the warning.

Step 5: playbooks - optional flags, automatic synthesis

You do not need to decide whether a session "deserves" a playbook: a teach on a family without one auto-synthesizes a playbook_candidate from the session's journal, and the next session judges it via confirm/reject. Attach explicit playbook flags only when you already hold choreography worth recording verbatim - workarounds the CLI didn't surface (silently-dropped flags, undocumented params, pagination tricks, payload gotchas). Prefer the integrated one-call form - record the resource learning and the playbook in the same teach invocation:

bash
# Common case: record both the resource learning AND the playbook in one call.
unipile-pp-cli teach \
  --query "<user's question>" \
  --resource <id> \
  --playbook-file ~/playbooks/<shape>.json \
  --playbook-notes-file ~/playbooks/<shape>-notes.md
# (append shell `&` to background it)

# Alternate: playbook-only (no resource to record alongside).
unipile-pp-cli teach-playbook \
  --query "<user's question>" \
  --playbook-file ~/playbooks/<shape>.json \
  --notes-file ~/playbooks/<shape>-notes.md

Playbook files are JSON with steps, entity_slots, expected_tool_calls. Notes files are markdown carrying the gotchas verbatim. File-free callers (MCP-only agents) pass the same content inline: --playbook-json and --playbook-notes on the integrated teach form, --playbook-json and --notes on teach-playbook. On the integrated teach form, the playbook flags are optional - omit them entirely for a resource-only teach. On the standalone teach-playbook form, at least one of the playbook and notes flags must be set; both empty is rejected. Playbooks are keyed on the structural query family (entities stripped) so a recipe taught from one entity-shaped query applies to every other query of the same shape, with slots_resolved binding the live query's canonical at recall time.

When you DO find a playbook on a future recall, treat it as ground truth: replay the steps with slots_resolved substitutions, skip the discovery that the choreography already documents, and read notes before any step.

Step 6: playbook amend & when your debug response identifies a correction

If your debug-protocol response identifies a concrete correction the notes or playbook should know — a workaround, an undocumented endpoint shape, a stale field name, observed schema drift, an empty-payload fallback — fire playbook amend BEFORE emitting your user-facing response. Same fire-and-forget posture as teach.

bash
unipile-pp-cli playbook amend \
  --query "<exact recall query string>" \
  --add-note "<your concrete correction>"
# (append shell `&` to background it)

What counts as worth amending: a behavior you OBSERVED this session that future-you would benefit from knowing. Examples worth amending:

  • A workaround for a CLI surface that silently drops or misorders a flag.
  • An undocumented endpoint shape (response wrapped in {meta, results}, payload nested two levels deeper than the docs claim).
  • Observed schema drift (a field renamed, an index that shifted between seasons, a category label that the API now returns lower-cased).

What does NOT belong in notes:

  • The year-specific or entity-specific answer to the user's question. That's the response, not a learning.
  • Per-team / per-athlete / per-row data the playbook already retrieves at runtime.
  • Statements that paraphrase what the existing notes already say.

The amend command appends to the family's existing notes with a timestamped marker ([amend YYYY-MM-DDTHH:MMZ]: <text>). Multiple amends accumulate; the audit trail is visible. If no playbook exists yet for the family, amend creates a notes-only one (so cold-start corrections still land).

PII discipline for amend notes

playbook amend notes are designed to potentially flow upstream as shared knowledge in future versions of the Printing Press. Keep them clean of user-identifying content so the upstream-contribution path stays open without retroactive scrubbing:

  • Do NOT embed paths to user filesystems, personal API keys or tokens, user email addresses, user GitHub handles, or specific query histories tied to a single user.
  • Acceptable: endpoint shapes, undocumented field names, API gotchas, observed schema drift, workarounds for CLI surfaces, generalizable pagination or retry tactics.

If a correction is only meaningful with user-specific context, it belongs in a personal note, not in the playbook amend.

Measuring the loop

unipile-pp-cli learnings stats reports recall hit rate, teach-to-reuse, playbook resolution rate, and candidate confirm/reject counts from the local learn_events table. Rates are null until they have a denominator; everything stays on this machine. Use it to check whether the loop is earning its keep for this CLI.

Disabling learning
  • --no-learn on a single command short-circuits both recall and the teach write path. Use for deterministic agent flows or tests that must not be affected by accumulated learnings.
  • UNIPILE_NO_LEARN=true in the environment globally disables the pipeline.

Agent Feedback

When you (or the agent) notice something off about this CLI, record it:

unipile-pp-cli feedback "the --since flag is inclusive but docs say exclusive"
unipile-pp-cli feedback --stdin < notes.txt
unipile-pp-cli feedback list --json --limit 10

Entries are stored locally as feedback.jsonl under the resolved data dir. They are never POSTed unless UNIPILE_FEEDBACK_ENDPOINT is set AND either --send is passed or UNIPILE_FEEDBACK_AUTO_SEND=true. Default behavior is local-only.

Write what surprised you, not a bug report. Short, specific, one line: that is the part that compounds.

Output Delivery

Every command accepts --deliver <sink>. The output goes to the named sink in addition to (or instead of) stdout, so agents can route command results without hand-piping. Three sinks are supported:

SinkEffect
stdoutDefault; write to stdout only
file:<path>Atomically write output to <path> (tmp + rename)
webhook:<url>POST the output body to the URL (application/json or application/x-ndjson when --compact)

Unknown schemes are refused with a structured error naming the supported set. Webhook failures return non-zero and log the URL + HTTP status on stderr.

Named Profiles

A profile is a saved set of flag values, reused across invocations. Use it when a scheduled or recurring agent reuses the same saved flags while providing different input each run.

unipile-pp-cli profile save briefing --json
unipile-pp-cli --profile briefing accounts list
unipile-pp-cli profile list --json
unipile-pp-cli profile show briefing
unipile-pp-cli profile delete briefing --yes

Explicit flags always win over profile values; profile values win over defaults. agent-context lists all available profiles under available_profiles so introspecting agents discover them at runtime.

Exit Codes

CodeMeaning
0Success
2Usage error (wrong arguments)
3Resource not found
4Authentication required
5API error (upstream issue)
7Rate limited (wait and retry)
10Config error

Argument Parsing

Parse $ARGUMENTS:

  1. Empty, help, or --help → show unipile-pp-cli --help output
  2. Starts with install → ends with mcp → MCP installation; otherwise → see Prerequisites above
  3. Anything else → Direct Use (execute as CLI command with --agent)

MCP Server Installation

  1. Install the MCP server:
    bash
    go install github.com/mvanhorn/printing-press-library/library/social-and-messaging/unipile/cmd/unipile-pp-mcp@latest
  2. Register with Claude Code:
    bash
    claude mcp add unipile-pp-mcp -- unipile-pp-mcp
  3. Verify: claude mcp list

Direct Use

  1. Check if installed: which unipile-pp-cli If not found, offer to install (see Prerequisites at the top of this skill).
  2. Match the user query to the best command from the Unique Capabilities and Command Reference above.
  3. Execute with the --agent flag:
    bash
    unipile-pp-cli <command> [subcommand] [args] --agent
  4. If ambiguous, drill into subcommand help: unipile-pp-cli <command> --help.

© mvanhorn, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in cli-skills/pp-unipile of mvanhorn/printing-press-library.

Open the folder on GitHubat commit d9a1696

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Works with

Questions about Pp Unipile

What does Pp Unipile do?

Every Unipile endpoint as a typed command, plus a local mirror that makes cross-provider search possible and an invitation ledger that shows how much LinkedIn headroom you have left. Pp Unipile is an agent skill from mvanhorn/printing-press-library. Every Unipile endpoint as a typed command, plus a local mirror that makes cross-provider search possible and an invitation ledger that shows how much LinkedIn headroom you have left.

When should I use Pp Unipile?

Pp Unipile fits situations like: phrases: check my unified inbox; who accepted my LinkedIn invitations; how many invitations can I still send today; find conversations nobody replied to.

How do I install Pp Unipile in Claude Code?

Run `npx skills add mvanhorn/printing-press-library --skill pp-unipile -a claude-code`. Or copy the skill folder (cli-skills/pp-unipile in mvanhorn/printing-press-library) into .claude/skills/pp-unipile in your project. Claude Code loads it when a task matches its description.

How do I install Pp Unipile in Codex?

Run `npx skills add mvanhorn/printing-press-library --skill pp-unipile -a codex`. Or copy the skill folder (cli-skills/pp-unipile in mvanhorn/printing-press-library) into .agents/skills/pp-unipile in your project. Codex loads it when a task matches its description.

Can I use Pp Unipile in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add mvanhorn/printing-press-library --skill pp-unipile -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/pp-unipile, .gemini/skills/pp-unipile, .github/skills/pp-unipile and .opencode/skills/pp-unipile in your project.

What does Pp Unipile need to run?

Going by SKILL.md and its folder, Pp Unipile needs the command-line tools its instructions call (go, claude and npx) and credentials named UNIPILE_API_KEY. Our summary lists: Node.js. Its frontmatter pre-approves these tools: Read, Bash.

Does Pp Unipile access the network?

SKILL.md contains no URLs. Its commands use npx, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Pp Unipile safe to install?

Our automated static check of SKILL.md found notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.

What licence does Pp Unipile use?

Pp Unipile is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Pp Unipile use?

About 8.9k tokens (SKILL.md is roughly 36k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Pp Unipile?

Skills that share tags, products or a category with Pp Unipile: Li Inbox (Jakeschincariol/linkedin-agent-skill, 1.7k stars), Curviate Inbox (davila7/claude-code-templates, 33k stars), Linkedin Inbox (sundial-org/awesome-openclaw-skills, 663 stars) and Linkedin Monitor (sundial-org/awesome-openclaw-skills, 663 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Pp Unipile?

mvanhorn (a GitHub user) maintains it in mvanhorn/printing-press-library, which has 2,056 GitHub stars. The repository holds 506 skills in this directory. The repository was last updated on October 9, 2026.

Source: mvanhorn/printing-press-library on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.