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mcp-geo-long-horizon-summary

mcp-geo-long-horizon-summary is a skill for Codex from chris-page-gov/mcp-geo. It costs 30 tokens per session (545 once invoked), scanned A, original, MIT.

A skill that creates a metrics report about Codex work on the mcp-geo repository from local Codex session logs. The report includes a summary image and a Markdown file, with an optional JSON data file.

In plain words
What is it for?
Use it to generate dated reports filtered to mcp-geo, including a summary SVG, Markdown report, and optional JSON metrics payload.
Why use it?
It turns raw session logs into a consistent view of runtime, token use, tool calls, and other work measurements.

Skill for Codex

Written for Codex: reads ~/.codex or $CODEX_HOME. Also seen: mentions Codex.

Needs its repository: it runs a file that does not travel with it, so clone the repository first. The line is python3 scripts/codex_long_horizon_summary.py \.

not rated 3repo 1mo ago A scan 30 tokens original MIT

Good fit Use it to generate dated reports filtered to mcp-geo, including a summary SVG, Markdown report, and optional JSON metrics payload.

Compare 6 skills from other repositories ↓
View source ↗ chris-page-gov/mcp-geo
Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo
git clone --depth 1 https://github.com/chris-page-gov/mcp-geo
agentmods
npx agentmods add skills/chris-page-gov/mcp-geo/mcp-geo-long-horizon-summary

Made for: Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for mcp-geo-long-horizon-summary

README.md
[![agentmods](https://agentmods.dev/badge/skills/chris-page-gov/mcp-geo/mcp-geo-long-horizon-summary/github.svg)](https://agentmods.dev/skills/chris-page-gov/mcp-geo/mcp-geo-long-horizon-summary)
Your own site
<a href="https://agentmods.dev/skills/chris-page-gov/mcp-geo/mcp-geo-long-horizon-summary"><img src="https://agentmods.dev/badge/skills/chris-page-gov/mcp-geo/mcp-geo-long-horizon-summary/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for mcp-geo-long-horizon-summary

Your own site · 80×15
<a href="https://agentmods.dev/skills/chris-page-gov/mcp-geo/mcp-geo-long-horizon-summary"><img src="https://agentmods.dev/badge/skills/chris-page-gov/mcp-geo/mcp-geo-long-horizon-summary.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 30 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 545 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00030 $0.00545
Opus 5 $0.00015 $0.00272
Sonnet 5 $0.00006 $0.00109
Haiku 4.5 $0.00003 $0.00055

Measured 12d ago against content hash d218207b161f, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

mcp-geo-long-horizon-summary scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/run_summary.sh), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/mcp-geo-long-horizon-summary/SKILL.md · 65 lines

What it actually says

MCP Geo Long Horizon Summary

Use this skill when a user asks for an OpenAI "Long horizon tasks" style summary for MCP Geo work (runtime, tokens, tool calls, patch volume, compactions, etc.).

Inputs

  • Codex session logs under $CODEX_HOME (defaults to ~/.codex).
  • Repo filter (default: mcp-geo).

Output

  • Summary-card SVG image in docs/reports/.
  • Markdown report in docs/reports/ that opens with the summary image.
  • Optional JSON metrics payload for downstream dashboards.

Runbook

  1. Generate report:
python3 scripts/codex_long_horizon_summary.py \
  --repo-filter mcp-geo \
  --summary-svg-output docs/reports/mcp_geo_codex_long_horizon_summary_$(date -u +%F).svg \
  --summary-title "Codex MCP-Geo Summary" \
  --output docs/reports/mcp_geo_codex_long_horizon_summary_$(date -u +%F).md \
  --json-output docs/reports/mcp_geo_codex_long_horizon_summary_$(date -u +%F).json
  1. If needed, point to a non-default Codex home:
python3 scripts/codex_long_horizon_summary.py \
  --codex-home /path/to/.codex \
  --repo-filter mcp-geo
  1. Validate that the report includes these headline metrics:
  • Active runtime
  • Wall-clock span
  • Token usage (input/output)
  • Cached input reused
  • Tool calls (shell + patch calls)
  • Patch volume (added lines from apply_patch)
  • Peak single-step tokens
  • Auto context compactions

Notes

  • Sessions are included when session_meta.payload.cwd contains the repo filter.
  • Patch volume is estimated from apply_patch payloads and will not include edits made through other methods.
  • Token totals use the latest token_count.total_token_usage snapshot per session.
  • Graphic output uses deterministic template file skills/mcp-geo-long-horizon-summary/templates/summary_card.svg.tmpl with slot-based number substitution.
  • Template is tuned for slide import (1920x1080, 16:9) and uses PowerPoint-friendly inline text styling (no CSS font shorthand) to keep text sizing consistent.
Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 12d ago First seen · 65 lines · 30 tokens per session scan A d218207b161f

Subscribe to this mod's changes

mcp-geo-long-horizon-summary is a skill published in the GitHub repository chris-page-gov/mcp-geo (3 stars, last pushed 1mo ago), licensed MIT. It adds 30 tokens to every session and 545 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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