Zameen — Printing Press CLI
Prerequisites: Install the CLI
This skill drives the zameen-pp-cli binary. You must verify the CLI is installed before invoking any command from this skill. If it is missing, install it first:
- Install via the Printing Press installer. It defaults binaries to
$HOME/.local/binon macOS/Linux and%LOCALAPPDATA%\Programs\PrintingPress\binon Windows:npx -y @mvanhorn/printing-press-library install zameen --cli-only - Verify:
zameen-pp-cli --version - Ensure the reported install directory is on
$PATHfor 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:
go install github.com/mvanhorn/printing-press-library/library/commerce/zameen/cmd/zameen-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.
Zameen.com has no API and no alerts, so investors and agents refresh the same search pages by hand every day. This CLI searches with real filters (price, beds, area in Marla/Kanal, city/area), mirrors results into a local SQLite store, and diffs runs to surface new listings and price drops. Built-in comps, deals, and aging turn that store into area medians, below-market plot-file detection, and days-on-market leverage.
When to Use This CLI
Use this CLI to search and monitor Pakistan property listings from a terminal or an agent: parametric search across buy/rent, homes/plots/commercial; keeping a local SQLite mirror for offline comps, deals, and aging; and tracking a saved search over time for new listings and price drops. It is strongest for market research, deal-hunting (below-market plot files, aging inventory), and area comps.
Anti-triggers
Do not use this CLI for:
- Do not use this CLI to post, edit, or delete listings — it is read-only over Zameen's public search.
- Do not use it to access a Zameen account, favorites, or saved alerts — it uses no login and touches no account data.
- Do not use it for property portals outside Pakistan (Zillow, Rightmove, Bayut) — it is Zameen-specific.
- Do not use it as a legal source of truth for prices or ownership — listing data is asking prices from public pages.
Unique Capabilities
These capabilities aren't available in any other tool for this API.
Local state that compounds
watch— Re-run a saved search and see exactly which listings are new and which dropped in price since last time.Reach for this to monitor a market over time instead of re-eyeballing search pages; it answers 'what changed since yesterday?' which no single fetch can.
zameen-pp-cli watch dha-homes --city Islamabad --purpose buy --type Homes --area DHA_Defence --agentcomps— Median price, price-per-Marla, and inventory count for an area or society, computed from your synced listings.Use for area-level comps sheets and market rollups before a pitch or an offer.
zameen-pp-cli comps --city Lahore --area DHA_Defence --agent --select area,median_price,median_price_per_marla,countagencies— Ranks agencies by listing count and median asking price in an area, from your synced listings.Use to see who dominates supply in a society before choosing an agent or gauging market concentration.
zameen-pp-cli agencies --city Karachi --agent
Deal-finding
deals— Ranks scanned listings by how far under the area's price-per-Marla they sit and flags below-market files.Reach for this to surface underpriced plot files in Pakistan's plot-flipping market before another dealer grabs them.
zameen-pp-cli deals --city Islamabad --area DHA_Defence --type Plots --agentaging— Lists the longest-standing inventory by days-on-market, derived from each listing's update timestamp.Use to find sellers likely to negotiate — inventory that has sat on the market longest.
zameen-pp-cli aging --city Islamabad --days 90 --agent
Command Reference
listings — Search and read Zameen property listings
zameen-pp-cli listings <category> <location> <page>— Fetch one page of Zameen search results (server-rendered; listings parsed from the embedded page state)
Finding the right command
When you know what you want to do but not which command does it, ask the CLI directly:
zameen-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
Search homes for sale under budget
zameen-pp-cli find --city Islamabad --purpose buy --type Homes --min-beds 3 --max-price 30000000 --sort price-asc
Three-plus-bed homes for sale in Islamabad under 3 crore, cheapest first.
Bulk-export a search to CSV
zameen-pp-cli find --city Lahore --purpose rent --type Homes --max-scan-pages 10 --csv > lahore-rentals.csv
Scan up to 10 pages of Lahore rentals and write a CSV for a spreadsheet.
Find below-market plot files
zameen-pp-cli deals --city Islamabad --area DHA_Defence --type Plots --agent
Rank DHA Islamabad plot files by how far under the area price-per-Marla they sit, as structured output for an agent.
Narrow a verbose listing payload for an agent
zameen-pp-cli find --city Karachi --purpose buy --type Homes --agent --select external_id,title,price,area_marla,beds,location
Return only the fields an agent needs from each listing instead of the full record, keeping context small.
Monitor a saved search for changes
zameen-pp-cli watch dha-homes --city Islamabad --purpose buy --type Homes --area DHA_Defence
On each run, diff against the last snapshot to show new listings and price drops.
Auth Setup
No account or API key needed. Zameen's public search is served as standard HTTP; the CLI reads listing data straight from the server-rendered search pages.
Run zameen-pp-cli doctor to verify setup.
Agent Mode
Add --agent to any command. Expands to: --json --compact --no-input --no-color --yes.
Pipeable — JSON on stdout, errors on stderr
Filterable —
--selectkeeps a subset of fields. Dotted paths descend into nested structures; arrays traverse element-wise. Critical for keeping context small on verbose APIs:zameen-pp-cli listings Homes Islamabad-3 1 --agent --select id,name,statusPreviewable —
--dry-runshows the request without sendingOffline-friendly — sync/search commands can use the local SQLite store when available
Non-interactive — never prompts, every input is a flag
Read-only — do not use this CLI for create, update, delete, publish, comment, upvote, invite, order, send, or other mutating requests
Response envelope
Commands that read from the local store or the API wrap output in a provenance envelope:
{
"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 setZAMEEN_HOME=<dir>to relocate all four path kinds under one root.Use per-kind env vars only when a specific kind must diverge:
ZAMEEN_CONFIG_DIR,ZAMEEN_DATA_DIR,ZAMEEN_STATE_DIR,ZAMEEN_CACHE_DIR.Resolution order is per-kind env var,
--home,ZAMEEN_HOME, XDG (XDG_CONFIG_HOME,XDG_DATA_HOME,XDG_STATE_HOME,XDG_CACHE_HOME), then platform defaults.configcontains settings likeconfig.tomland profiles.datacontainscredentials.toml,data.db, cookies, and auth sidecars.statecontains persisted queries, jobs, andteach.log.cachecontains regenerable HTTP/cache files.Stored secrets live in
credentials.tomlunder the data dir. Existing legacyconfig.tomlsecrets are read for compatibility and leaveconfig.tomlon the first auth write.Run
zameen-pp-cli doctor --fail-on warnto surface path and credential-location warnings.agent-contextexposes a schema v4pathsblock for agents that need the resolved dirs.For MCP, pass relocation through the MCP host config. The MCP binary does not inherit CLI flags:
{ "mcpServers": { "zameen": { "command": "zameen-pp-mcp", "env": { "ZAMEEN_HOME": "/srv/zameen" } } } }
Fleet precedence: an inherited per-kind env var overrides an explicit --home for that kind. Use ZAMEEN_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 ZAMEEN_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.
Step 1: recall before any discovery
Before list/search/drill commands on a new user question, run:
zameen-pp-cli recall "<user's question>" --agent
The response envelope:
{
"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>", "zameen-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 `zameen-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; zameen-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 atconfidence<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 viaentity_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 acandidatessection. Handle it via the candidates branch in Step 2 before anything else.- 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:
zameen-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:
# Common case: record both the resource learning AND the playbook in one call.
zameen-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).
zameen-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.
zameen-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
zameen-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-learnon a single command short-circuits bothrecalland theteachwrite path. Use for deterministic agent flows or tests that must not be affected by accumulated learnings.ZAMEEN_NO_LEARN=truein the environment globally disables the pipeline.
Agent Feedback
When you (or the agent) notice something off about this CLI, record it:
zameen-pp-cli feedback "the --since flag is inclusive but docs say exclusive"
zameen-pp-cli feedback --stdin < notes.txt
zameen-pp-cli feedback list --json --limit 10
Entries are stored locally as feedback.jsonl under the resolved data dir. They are never POSTed unless ZAMEEN_FEEDBACK_ENDPOINT is set AND either --send is passed or ZAMEEN_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:
| Sink | Effect |
|---|---|
stdout |
Default; 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.
zameen-pp-cli profile save briefing --json
zameen-pp-cli --profile briefing listings Homes Islamabad-3 1
zameen-pp-cli profile list --json
zameen-pp-cli profile show briefing
zameen-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
| Code | Meaning |
|---|---|
| 0 | Success |
| 2 | Usage error (wrong arguments) |
| 3 | Resource not found |
| 5 | API error (upstream issue) |
| 7 | Rate limited (wait and retry) |
| 10 | Config error |
Argument Parsing
Parse $ARGUMENTS:
- Empty,
help, or--help→ showzameen-pp-cli --helpoutput - Starts with
install→ ends withmcp→ MCP installation; otherwise → see Prerequisites above - Anything else → Direct Use (execute as CLI command with
--agent)
MCP Server Installation
- Install the MCP server:
go install github.com/mvanhorn/printing-press-library/library/commerce/zameen/cmd/zameen-pp-mcp@latest - Register with Claude Code:
claude mcp add zameen-pp-mcp -- zameen-pp-mcp - Verify:
claude mcp list
Direct Use
- Check if installed:
which zameen-pp-cliIf not found, offer to install (see Prerequisites at the top of this skill). - Match the user query to the best command from the Unique Capabilities and Command Reference above.
- Execute with the
--agentflag:zameen-pp-cli <command> [subcommand] [args] --agent - If ambiguous, drill into subcommand help:
zameen-pp-cli <command> --help.