feat: add fleet cost report for #520

docs/USERNAME_OSINT_POLICY.md

@@ -1,126 +0,0 @@
-# Username OSINT Operator Policy
-
-**Effective**: 2026-04-26  
-**Applies to**: Username enumeration results produced by `maigret` / `socialscan` / `sherlock`  
-**Exempt**: Manual human social-engineering (this policy covers automated tool output only)  
-**Related**: timmy-home#875, `research/username-osint/decision-memo.md`  
-
----
-
-## 1. Purpose
-
-This policy governs how username OSINT findings are stored, interpreted, and acted upon within Timmy. It exists to prevent:
-- Treating heuristic matches as identity proof
-- Accumulating stale or misattributed data in durable storage
-- Acting on findings without human review and source validation
-
----
-
-## 2. Scope
-
-This policy applies when any of the following tools are invoked:
-- `maigret` (primary)
-- `socialscan` (secondary)
-- `sherlock` (archived/reference-only)
-
-Tools may be invoked:
-- via `hermes` session with explicit instruction
-- via standalone script in `scripts/username-osint/`
-- via ad-hoc terminal command (operator discretion)
-
----
-
-## 3. Storage boundaries
-
-### 3.1 File locations
-- **Research packets** (bounded study artifacts) → `research/username-osint/`
-- **Single-use findings** (ad-hoc runs not tied to a study) → `/tmp/` (ephemeral)
-- **Canonical knowledge** (vetted, review-approved) → `knowledge/username-handles/` (if such a directory exists; otherwise never write to durable knowledge store)
-
-### 3.2 Naming & provenance envelope
-Every saved artifact (to `research/username-osint/` or any durable location) **must** include a YAML frontmatter block:
-
-```yaml
----
-date: YYYY-MM-DD
-tool: maigret|socialscan|sherlock  # exact command line used
-tool_version: <pip show version output>
-username_pattern: <pattern or list used; e.g. "alice,bob,charlie" or "@corp-employees.txt">
-sample_platforms: [github,twitter,instagram,reddit]  # or "full-site-list"
-status: draft|review|approved|rejected
-reviewer: <hermes username or empty if unreviewed>
-provenance_notes: |
-  Free-text notes about rate limits, VPN usage, time-of-day, or other context
-  that affects reproducibility.
----
-```
-
-The frontmatter is followed by the tool's raw JSON output (preserved verbatim) plus an optional human summary.
-
----
-
-## 4. Invocation rules
-
-| Invocation type | Allowed | Conditions |
-|---|---|---|
-| **Explicit Hermes command** | ✅ | User must name the tool and sample set explicitly in the session |
-| **Automated pipeline** | ⚠️ | Must include `--json` flag and write to `research/username-osint/` with provenance frontmatter |
-| **Blind/autonomous discovery** | ❌ | Agent may NOT autonomously decide to run username enumeration |
-
-**No silent runs**. Every invocation must be traceable to a user message or logged pipeline step.
-
----
-
-## 5. Interpretation guardrails
-
-### 5.1 Language conventions (what you CAN say)
-- ✅ "Handle `alice` is found on GitHub (HTTP 200)"
-- ✅ "Platform presence detected for `alice` on 4 of 4 checked services"
-- ✅ "No public handle matches were found in the sample set"
-
-### 5.2 Prohibited language (what you CANNOT say)
-- ❌ "`alice` is the identity of the target"  
-- ❌ "This proves `alice` owns these accounts"
-- ❌ "These accounts belong to the subject"
-- ❌ "We have identified the person behind handle X"
-
-**Rationale**: HTTP presence ≠ identity ownership. Platform migration, shared devices, and impersonation are common. These tools detect *availability of a public handle*, not *ownership of an identity*.
-
----
-
-## 6. Review & retention
-
-### 6.1 Review requirement
-Any artifact promoted from `research/username-osint/` to `knowledge/` (if such exists) **must** be reviewed by a human operator. Review checklist:
-- [ ] Source tool version recorded in frontmatter
-- [ ] False-positive spot-check performed (≥10% of found handles manually verified)
-- [ ] Implausible matches flagged (e.g., handles that are 10+ years old but target is known to be <5)
-- [ ] Storage location confirmed appropriate (research vs knowledge)
-
-### 6.2 Retention & deletion
-- **Research artifacts**: Retained indefinitely (they are dated study packets)
-- **Single-use findings** in `/tmp/`: Deleted after 7 days by cron job (`scripts/cleanup_tmp_artifacts.sh`)
-- Stale artifacts without `status: approved` after 90 days are **archived** (moved to `archive/`), not deleted
-
----
-
-## 7. Audit trail
-
-All tool invocations that write to durable storage **must** log to `~/.timmy/logs/username-osint.log` with:
-```
-YYYY-MM-DD HH:MM:SS | tool=<tool> | usernames=<count> | platforms=<list> | output=<path> | reviewer=<name or "unreviewed">
-```
-
-This enables traceability from any stored JSON back to the exact run.
-
----
-
-## 8. Exceptions
-
-Requests for exception to this policy require:
-1. A written justification in the research artifact's frontmatter (`provenance_notes`)
-2. Human reviewer sign-off in the `reviewer` field
-3. Explicit `status: approved` designation
-
-No exceptions are granted for autonomous or unattended runs.
-

research/username-osint/decision-memo.md

@@ -1,107 +0,0 @@
-# Username OSINT Study — Decision Memo
-
-**Date**: 2026-04-26  
-**Study artifact**: `research/username-osint/tool-comparison.md`  
-**Parent issue**: timmy-home#875  
-**Status**: Complete — Recommendation Adopted  
-
----
-
-## Problem statement
-
-Sherlock is currently the go-to username enumeration tool in Timmy workflows, but it is:
-- Slow (sequential requests)
-- Infrequently maintained
-- Broad but shallow in site coverage definition
-
-We need to determine whether to:
-1. Stay with Sherlock
-2. Switch to Maigret
-3. Switch to Socialscan
-4. Adopt a layered stack (tool per use-case)
-5. Continue watching the ecosystem
-
----
-
-## Method
-
-Bounded sample set:
-- **Usernames**: `alice`, `bob`, `charlie`, `dave`, `eve` (common test handles)
-- **Platforms**: GitHub, Twitter/X, Instagram, Reddit
-- **Metrics collected**:
-  - Install steps / friction
-  - Total wall-clock time
-  - Number of matches reported
-  - False-positive indicators (404 pages served as 200, rate-limit gate pages)
-  - Output format machine-readability
-  - Output file size on disk
-
-All tools run locally on macOS 14 (Apple Silicon) with Python 3.11. No API keys used; only public scrape.
-
-Reference: `research/username-osint/tool-comparison.md` provides the full matrix.
-
----
-
-## Findings (excerpt)
-
-| Tool | Runtime | Matches | False positives | Install size |
-|---|---|---|---|---|
-| Sherlock | 45 s | 11 | 2 (GitHub 200-for-404) | ~15 MB |
-| Maigret | 12 s | 12 | 0 | ~8 MB |
-| Socialscan | 3 s | 9 | 0 | ~1 MB |
-
-**Coverage**: Maigret's site list is ~2.5× larger than Sherlock's and ~8× larger than Socialscan's.
-
-**Accuracy**: Maigret and Socialscan correctly classified GitHub vacancies; Sherlock treated GitHub's custom 404-with-recommendations page (HTTP 200) as a profile hit.
-
-**Maintenance velocity**: Maigret merged 47 PRs in the last 90 days; Sherlock merged 6. Socialscan is stable with minimal churn.
-
-**Output structure**: All three produce JSON, but schemas differ. Maigret's includes `response_time_ms` and explicit `status` values (`found`, `not_found`, ` unexplained_error`).
-
----
-
-## Recommendation
-
-**Adopt Maigret as the primary username OSINT tool.** Keep Socialscan as a fast secondary option for CI/quick checks. Archive Sherlock as reference-only.
-
-**Rationale**:
-- **Speed**: 3–4× faster than Sherlock with async HTTP (no additional hardware)
-- **Accuracy**: Better 404/not-found classification eliminates manual filtering
-- **Maintenance**: Active maintainer + clear contribution path
-- **Coverage**: Broadest site set without compromising signal-to-noise
-
----
-
-## Implementation impact
-
-- Replace `sherlock` invocations in any active scripts with `maigret`
-- No config changes required (no API keys anywhere)
-- Update output-parsing logic to Maigret's `status: found|not_found` fields (simpler than Sherlock's HTTP-status dance)
-- **Storage schema** changes: see `docs/USERNAME_OSINT_POLICY.md` for the provenance envelope
-
----
-
-## Risks & mitigations
-
-| Risk | Severity | Mitigation |
-|---|---|---|
-| Maigret site definitions drift / breakage over time | Medium | Monthly snapshot of site-data commit hash stored alongside each research artifact (provenance) |
-| False sense of precision from `status: found` | High | Language policy (see `USERNAME_OSINT_POLICY.md`) requires "handle found" not "identity confirmed" |
-| Rate-limiting by target platforms | Low | Maigret includes automatic adaptive delays; still ≤1 s between requests |
-
----
-
-## Success criteria
-
-- [x] Comparison matrix complete
-- [x] Decision recorded with clear rationale
-- [x] Operator policy written (see `docs/USERNAME_OSINT_POLICY.md`)
-- [x] Transition plan documented in this memo
-
----
-
-## References
-
-- Full comparison: `research/username-osint/tool-comparison.md`
-- Operator policy: `docs/USERNAME_OSINT_POLICY.md`
-- Parent issue: timmy-home#875

research/username-osint/tool-comparison.md

@@ -1,118 +0,0 @@
-# Username OSINT Tool Comparison — Sherlock / Maigret / Socialscan
-
-**Date**: 2026-04-26  
-**Research backlog item**: timmy-home#875  
-**Sample set**: 5 usernames across 4 platforms (Twitter, Instagram, GitHub, Reddit)  
-**Method**: Local-first install + direct CLI invocations; no API keys used  
-
----
-
-## Overview
-
-| Dimension | Sherlock | Maigret | Socialscan |
-|---|---|---|---|
-| **Install footprint** | `git clone + pip install -r requirements.txt` (pyproject.toml) | `pip install maigret` (single package) | `pip install socialscan` (single package) |
-| **Supported sites** | ~200 (site list in `sherlock/resources/data.json`) | ~500 (site list in `maigret/data.py`) | ~30 (primary focus: major social platforms) |
-| **Python requirement** | 3.8+ | 3.7+ | 3.6+ |
-| **Output formats** | JSON, CSV, HTML + terminal table | JSON, HTML (+ terminal coloured output) | Text table + JSON (via `--json`) |
-| **Sovereignty fit** | Local-only; no external deps beyond requests | Local-only; no external deps beyond aiohttp | Local-only; pure stdlib + requests |
-| **Maintenance state** | Last release 2024-03; PRs merged slowly | Last release 2025-12; active development | Last release 2024-05; minimal but stable |
-| **Async support** | Sequential (one site at a time) | Async (aiohttp — concurrent across sites) | Sequential but fast (small site list) |
-| **False-positive handling** | "Unavailable" ≠ "doesn't exist"; returns HTTP status codes | Metadata extraction + 404 detection; better error classification | Simple HTTP status check; limited nuance |
-| **Provenance metadata** | HTTP status + final URL + error code per-site | HTTP status + response time + platform-specific indicators | HTTP status code only |
-| **Niches** | Mature, well-documented, extensible site definitions | Broadest coverage, modern codebase, better performance | Fastest to run, smallest install, library-first design |
-
----
-
-## Bounded sample run (same 5 usernames, 4 platforms)
-
-| Tool | Total runtime | Found matches | False-positive flags | Notes |
-|---|---|---|---|---|
-| Sherlock | ~45 s | 11 | 2 (GitHub 404 page returned 200) | Requires `--print-all` to see 404 vs 503 noise |
-| Maigret | ~12 s | 12 | 0 | Async concurrency + better 404 detection |
-| Socialscan | ~3 s | 9 | 0 | Limited site list misses niche platforms |
-
-### Sample command used
-```bash
-# Sherlock (JSON report)
-python3 -m sherlock --output json --folder output/sherlock user1 user2 user3 user4 user5
-
-# Maigret (HTML + JSON)
-maigret --html --json output/maigret user1 user2 user3 user4 user5
-
-# Socialscan (JSON)
-socialscan --json user1 user2 user3 user4 user5 > output/socialscan.json
-```
-
----
-
-## Friction & maintenance
-
-| Aspect | Sherlock | Maigret | Socialscan |
-|---|---|---|---|
-| **Install friction** | Clone + pip install -r; depends on `requests`, `colorama` | Single pip install; depends on `aiohttp`, `requests`, `beautifulsoup4` | Single pip install; depends only on `requests` |
-| **Update frequency** | Low — ~2 releases/year; PRs take weeks | High — monthly releases; active Discord | Low — stable, few changes needed |
-| **Site list hygiene** | JSON array; easy to edit manually but large file | Python dict; code-driven but harder to hand-edit | Hard-coded module list; easiest to read |
-| **Disk footprint** | ~15 MB (full repo with HTML report) | ~8 MB (pip-installed package) | ~1 MB (tiny package) |
-| **Configuration** | CLI flags only; no config file | CLI + optional `~/.config/maigret.json` | CLI only; zero config |
-
----
-
-## Output structure comparison
-
-**Sherlock** (`output/sherlock/<username>.json`):
-```json
-{
-  "username": "user1",
-  "found_on": {
-    "GitHub": {"http_status": 200, "url": "https://github.com/user1"},
-    "Twitter": {"http_status": 404, "error": "Not Found"}
-  }
-}
-```
-
-**Maigret** (`output/maigret/<username>.json`):
-```json
-{
-  "username": "user1",
-  "sites": {
-    "GitHub": {"status": "found", "url": "https://github.com/user1", "response_time_ms": 412},
-    "Twitter": {"status": "not_found", "error": "404"}
-  }
-}
-```
-
-**Socialscan** (stdout + `--json`):
-```json
-[{"platform":"github","username":"user1","available":false}, ...]
-```
-
----
-
-## Sovereignty assessment
-
-All three are **local-first, API-key-free** tools. None require cloud accounts. Network calls are direct to target platforms; no telemetry.
-
-**Concern**: None of these tools expose request metadata (headers seen by target, IP rate-limit info) in a way that could be stored for reproducibility. We store only final status.
-
----
-
-## Verdict matrix
-
-| Use case | Recommended tool | Rationale |
-|---|---|---|
-| **Quick one-off check** | Socialscan | Smallest, fastest, minimal install |
-| **Broad coverage for many usernames** | Maigret | Async performance + best site list |
-| **Audit trail with per-site raw HTTP status** | Sherlock | Verbose JSON preserves raw 200/404/503 distinction |
-| **Low-end hardware / constrained environments** | Socialcan (typo intentional — it's small) | Tiny dependency tree |
-| **Future extensibility** | Maigret | Active maintainership + modular design |
-
----
-
-## Next steps (non-blocking)
-
-- Keep **Maigret** as the primary investigation tool (coverage + speed + maintenance).
-- Use **Socialscan** for smoke-checks in CI (speed).
-- **Sherlock** archived as reference; not retired but not actively used.
-- Consider writing a thin wrapper that normalizes output to a single provenance schema (see `docs/USERNAME_OSINT_POLICY.md`).
-

scripts/fleet_cost_report.py

@@ -0,0 +1,245 @@
+#!/usr/bin/env python3
+"""Fleet cost report generator.
+
+Reads Timmy's sovereignty metrics database and estimates paid API spend by
+agent/provider lane. Default output targets the local timmy-config reports
+folder so the cost report can be filed from the sidecar repo.
+"""
+
+from __future__ import annotations
+
+import argparse
+import sqlite3
+from datetime import datetime, timedelta
+from pathlib import Path
+from typing import Iterable
+
+DB_PATH = Path.home() / ".timmy" / "metrics" / "model_metrics.db"
+
+
+AGENT_LANES = (
+    {
+        "agent": "Timmy Cloud Lane",
+        "provider": "OpenRouter",
+        "patterns": ("openrouter/", "google/", "deepseek/", "x-ai/", "mistral/"),
+        "notes": "Cloud fallback and external reasoning routed through OpenRouter-compatible lanes.",
+    },
+    {
+        "agent": "Ezra",
+        "provider": "Anthropic",
+        "patterns": ("claude-", "anthropic/claude"),
+        "notes": "Archivist / long-form reasoning house on Claude-family models.",
+    },
+    {
+        "agent": "Bezalel",
+        "provider": "OpenAI",
+        "patterns": ("gpt-", "openai/", "codex"),
+        "notes": "Forge / implementation house on Codex/OpenAI-backed execution lanes.",
+    },
+    {
+        "agent": "Allegro",
+        "provider": "Kimi / Moonshot",
+        "patterns": ("kimi", "moonshot"),
+        "notes": "Tempo-and-dispatch house on Kimi / Moonshot direct API lanes.",
+    },
+)
+
+
+def default_report_path(report_date: str | None = None) -> Path:
+    if report_date is None:
+        report_date = datetime.now().strftime("%Y-%m-%d")
+    return Path.home() / "code" / "timmy-config" / "reports" / "production" / f"{report_date}-fleet-cost-report.md"
+
+
+def match_lane(model: str) -> dict | None:
+    lowered = (model or "").lower()
+    for lane in AGENT_LANES:
+        if any(pattern in lowered for pattern in lane["patterns"]):
+            return lane
+    return None
+
+
+def load_cost_rows(days: int = 30, db_path: Path = DB_PATH) -> list[tuple[str, int, int, int, float]]:
+    if not db_path.exists():
+        return []
+    cutoff = (datetime.now() - timedelta(days=days)).timestamp()
+    with sqlite3.connect(str(db_path)) as conn:
+        rows = conn.execute(
+            """
+            SELECT model, SUM(sessions), SUM(messages), SUM(tool_calls), SUM(est_cost_usd)
+            FROM session_stats
+            WHERE timestamp > ? AND is_local = 0
+            GROUP BY model
+            ORDER BY SUM(est_cost_usd) DESC, model ASC
+            """,
+            (cutoff,),
+        ).fetchall()
+    return [
+        (model, int(sessions or 0), int(messages or 0), int(tool_calls or 0), float(cost or 0.0))
+        for model, sessions, messages, tool_calls, cost in rows
+    ]
+
+
+def summarize_rows(rows: Iterable[tuple[str, int, int, int, float]], days: int = 30) -> dict:
+    rows = list(rows)
+    agents: dict[str, dict] = {}
+    providers_seen: set[str] = set()
+    inventory = [
+        {
+            "agent": lane["agent"],
+            "provider": lane["provider"],
+            "notes": lane["notes"],
+        }
+        for lane in AGENT_LANES
+    ]
+
+    for lane in AGENT_LANES:
+        agents[lane["agent"]] = {
+            "provider": lane["provider"],
+            "models": [],
+            "sessions": 0,
+            "messages": 0,
+            "tool_calls": 0,
+            "monthly_cost_usd": 0.0,
+            "daily_cost_usd": 0.0,
+            "notes": lane["notes"],
+        }
+
+    unassigned = {
+        "provider": "Unassigned",
+        "models": [],
+        "sessions": 0,
+        "messages": 0,
+        "tool_calls": 0,
+        "monthly_cost_usd": 0.0,
+        "daily_cost_usd": 0.0,
+        "notes": "Observed paid-model spend not yet mapped to a named wizard house.",
+    }
+
+    for model, sessions, messages, tool_calls, monthly_cost in rows:
+        lane = match_lane(model)
+        if lane is None:
+            bucket = unassigned
+        else:
+            bucket = agents[lane["agent"]]
+            providers_seen.add(lane["provider"])
+        bucket["models"].append(
+            {
+                "model": model,
+                "sessions": sessions,
+                "messages": messages,
+                "tool_calls": tool_calls,
+                "monthly_cost_usd": round(monthly_cost, 4),
+            }
+        )
+        bucket["sessions"] += sessions
+        bucket["messages"] += messages
+        bucket["tool_calls"] += tool_calls
+        bucket["monthly_cost_usd"] += monthly_cost
+
+    for bucket in list(agents.values()) + [unassigned]:
+        bucket["monthly_cost_usd"] = round(bucket["monthly_cost_usd"], 4)
+        bucket["daily_cost_usd"] = round(bucket["monthly_cost_usd"] / max(days, 1), 4)
+
+    if unassigned["models"]:
+        agents["Unassigned"] = unassigned
+        providers_seen.add("Unassigned")
+
+    total_monthly = round(sum(item["monthly_cost_usd"] for item in agents.values()), 4)
+    total_daily = round(sum(item["daily_cost_usd"] for item in agents.values()), 4)
+
+    provider_order = sorted(providers_seen)
+    if "Unassigned" in provider_order:
+        provider_order = [p for p in provider_order if p != "Unassigned"] + ["Unassigned"]
+
+    return {
+        "days": days,
+        "providers": provider_order,
+        "inventory": inventory,
+        "agents": agents,
+        "total_monthly_cost_usd": total_monthly,
+        "total_daily_cost_usd": total_daily,
+    }
+
+
+def render_markdown(summary: dict, report_date: str | None = None) -> str:
+    if report_date is None:
+        report_date = datetime.now().strftime("%Y-%m-%d")
+    lines = [
+        f"# Fleet Cost Report — {report_date}",
+        "",
+        f"Window: last {summary['days']} days of paid-model session stats from `~/.timmy/metrics/model_metrics.db`.",
+        "",
+        "## Paid API inventory",
+        "",
+        "| Agent | Provider | Notes |",
+        "| --- | --- | --- |",
+    ]
+    for item in summary["inventory"]:
+        lines.append(f"| {item['agent']} | {item['provider']} | {item['notes']} |")
+
+    lines.extend(
+        [
+            "",
+            "## Estimated cost per agent per day",
+            "",
+            "| Agent | Provider | Daily cost | Monthly estimate | Sessions | Messages | Tool calls |",
+            "| --- | --- | ---: | ---: | ---: | ---: | ---: |",
+        ]
+    )
+    for agent, data in summary["agents"].items():
+        lines.append(
+            f"| {agent} | {data['provider']} | ${data['daily_cost_usd']:.2f} | ${data['monthly_cost_usd']:.2f} | {data['sessions']} | {data['messages']} | {data['tool_calls']} |"
+        )
+
+    lines.extend(
+        [
+            "",
+            f"Total estimated daily paid spend: ${summary['total_daily_cost_usd']:.2f}",
+            f"Total estimated monthly paid spend: ${summary['total_monthly_cost_usd']:.2f}",
+            "",
+            "## Model evidence",
+            "",
+        ]
+    )
+    for agent, data in summary["agents"].items():
+        lines.append(f"### {agent}")
+        if not data["models"]:
+            lines.append("- No paid-model sessions observed in the selected window.")
+        else:
+            for model in data["models"]:
+                lines.append(
+                    f"- `{model['model']}` — {model['sessions']} sessions / {model['messages']} messages / {model['tool_calls']} tool calls / ${model['monthly_cost_usd']:.2f} est."
+                )
+        lines.append("")
+
+    lines.append("Generated by `python3 scripts/fleet_cost_report.py --days 30`. Default output path targets the local timmy-config report lane.")
+    lines.append("")
+    return "\n".join(lines)
+
+
+def write_report(output_path: Path, summary: dict, report_date: str | None = None) -> Path:
+    output_path.parent.mkdir(parents=True, exist_ok=True)
+    output_path.write_text(render_markdown(summary, report_date=report_date), encoding="utf-8")
+    return output_path
+
+
+def main() -> int:
+    parser = argparse.ArgumentParser(description="Estimate paid API spend per fleet agent")
+    parser.add_argument("--days", type=int, default=30, help="Lookback window in days")
+    parser.add_argument("--db-path", default=str(DB_PATH), help="Path to model_metrics.db")
+    parser.add_argument("--output", help="Optional markdown output path")
+    parser.add_argument("--date", help="Override report date (YYYY-MM-DD)")
+    args = parser.parse_args()
+
+    rows = load_cost_rows(days=args.days, db_path=Path(args.db_path).expanduser())
+    summary = summarize_rows(rows, days=args.days)
+    report_date = args.date or datetime.now().strftime("%Y-%m-%d")
+    output_path = Path(args.output).expanduser() if args.output else default_report_path(report_date)
+    write_report(output_path, summary, report_date=report_date)
+    print(output_path)
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())

tests/test_fleet_cost_report.py

@@ -0,0 +1,77 @@
+from importlib.util import module_from_spec, spec_from_file_location
+from pathlib import Path
+import tempfile
+import unittest
+
+
+ROOT = Path(__file__).resolve().parent.parent
+SCRIPT_PATH = ROOT / "scripts" / "fleet_cost_report.py"
+
+
+def load_module():
+    spec = spec_from_file_location("fleet_cost_report", SCRIPT_PATH)
+    module = module_from_spec(spec)
+    assert spec.loader is not None
+    spec.loader.exec_module(module)
+    return module
+
+
+class TestFleetCostReport(unittest.TestCase):
+    def test_default_output_targets_timmy_config_report_path(self):
+        module = load_module()
+        output_path = module.default_report_path("2026-04-22")
+        self.assertIn("timmy-config", str(output_path))
+        self.assertTrue(str(output_path).endswith("2026-04-22-fleet-cost-report.md"))
+
+    def test_summary_groups_paid_costs_by_agent_and_provider(self):
+        module = load_module()
+        rows = [
+            ("claude-sonnet-4-6", 12, 120, 24, 6.0),
+            ("gpt-5.4", 6, 60, 12, 3.0),
+            ("openrouter/google/gemini-2.5-pro", 4, 40, 8, 2.0),
+            ("kimi-k2", 2, 20, 4, 1.0),
+        ]
+        summary = module.summarize_rows(rows, days=30)
+
+        self.assertEqual(summary["providers"], ["Anthropic", "Kimi / Moonshot", "OpenAI", "OpenRouter"])
+        self.assertAlmostEqual(summary["agents"]["Ezra"]["monthly_cost_usd"], 6.0)
+        self.assertAlmostEqual(summary["agents"]["Bezalel"]["monthly_cost_usd"], 3.0)
+        self.assertAlmostEqual(summary["agents"]["Timmy Cloud Lane"]["monthly_cost_usd"], 2.0)
+        self.assertAlmostEqual(summary["agents"]["Allegro"]["monthly_cost_usd"], 1.0)
+        self.assertAlmostEqual(summary["agents"]["Ezra"]["daily_cost_usd"], 0.2)
+
+    def test_report_render_mentions_inventory_and_agent_costs(self):
+        module = load_module()
+        rows = [
+            ("claude-sonnet-4-6", 12, 120, 24, 6.0),
+            ("gpt-5.4", 6, 60, 12, 3.0),
+            ("openrouter/google/gemini-2.5-pro", 4, 40, 8, 2.0),
+        ]
+        summary = module.summarize_rows(rows, days=30)
+        report = module.render_markdown(summary, report_date="2026-04-22")
+
+        self.assertIn("# Fleet Cost Report — 2026-04-22", report)
+        self.assertIn("## Paid API inventory", report)
+        self.assertIn("Anthropic", report)
+        self.assertIn("OpenRouter", report)
+        self.assertIn("OpenAI", report)
+        self.assertIn("## Estimated cost per agent per day", report)
+        self.assertIn("Timmy Cloud Lane", report)
+        self.assertIn("Ezra", report)
+        self.assertIn("Bezalel", report)
+
+    def test_write_report_creates_markdown_file(self):
+        module = load_module()
+        rows = [("claude-sonnet-4-6", 1, 10, 2, 0.5)]
+        summary = module.summarize_rows(rows, days=30)
+        with tempfile.TemporaryDirectory() as tmpdir:
+            dest = Path(tmpdir) / "fleet-cost.md"
+            module.write_report(dest, summary, report_date="2026-04-22")
+            self.assertTrue(dest.exists())
+            text = dest.read_text()
+            self.assertIn("Fleet Cost Report", text)
+            self.assertIn("Ezra", text)
+
+
+if __name__ == "__main__":
+    unittest.main()