Agent skill

Cortext Self Diagnosis

by grandamenium in grandamenium/cortextos

Diagnose cortextOS itself when the framework misbehaves — an agent has gone silent or wedged, agents are crash-looping, Telegram or agent-to-agent messages are not arriving, crons did not fire, an…

MITAuto-check passedProductivity & Automation

Install Cortext Self Diagnosis

skills CLI
$ npx skills add grandamenium/cortextos --skill cortext-self-diagnosis -a claude-code

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

GitHub CLI
$ gh skill install grandamenium/cortextos cortext-self-diagnosis --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/grandamenium/cortextos.git skills-src && mkdir -p .claude/skills && cp -r skills-src/community/skills/cortext-self-diagnosis .claude/skills/cortext-self-diagnosis && 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
cortext-self-diagnosis
GitHub stars
101
Token cost
~3.7k tokens
SKILL.md length
1,898 words
Files
7 (incl. scripts, references)
Skills in repo
55
Repo updated
First seen
Licence
MIT

At a glance

Diagnose cortextOS itself when the framework misbehaves — an agent has gone silent or wedged, agents are crash-looping, Telegram or agent-to-agent messages are not arriving, crons did not fire, an…

  • Works in 7 steps: Orient → Collect evidence → Read the right surface first → …
  • Tasks that involve Scheduled and recurring tasks
  • SKILL.md covers The one thing that makes this…, Stance: evidence before repair, Phase 0 — Orient and Phase 1 — Collect evidence, plus 7 more sections
  • Runs Shell and Python scripts from its folder; calls bash

What it does

Cortext Self Diagnosis is an agent skill from grandamenium/cortextos. Diagnose cortextOS itself when the framework misbehaves — an agent has gone silent or wedged, agents are crash-looping, Telegram or agent-to-agent messages are not arriving, crons did not fire, an agent re-onboards or shows offline when it is running, the daemon died, or the whole fleet is down. Walks a structured evidence-first investigation across logs, the message bus, state markers, and daemon output, then classifies the finding as local config vs. a genuine framework bug — and for real bugs, drives a fix…

Its SKILL.md is about 3.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 8 other files, including scripts and reference files (for example `references/surface-map.md`, `references/symptom-playbooks.md` and `references/test-matrix.md`).

It sits in Productivity & Automation, covering Scheduled and recurring tasks. It works with Telegram. The licence is MIT.

When your agent uses it

  • Tasks that involve Scheduled and recurring tasks

Example prompts

  • “why did my agent stop replying”
  • “is something broken”
  • “cortext is acting weird”
  • “/cortext-self-diagnosis”

Requirements

  • Python 3
  • A Bash shell

Workflow steps

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

  1. Orient
  2. Collect evidence
  3. Read the right surface first
  4. Hypothesis, then confirmation
  5. Classify the finding (the gate)
  6. Local fix
  7. Upstream path

What it can do on your machine

Read from SKILL.md and the folder at commit 6f93838. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 2 files in scripts/ (Shell and Python), which the agent can run.

    Shell commands in SKILL.md call:

    • bash

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

  • Network

    No URLs in SKILL.md.

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

  • Credentials

    Names no API keys, tokens, secrets or passwords.

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

Context cost

Cortext Self Diagnosis loads about 3.7k tokens when it runs, and up to ~14k if it reads all its reference files. Until then it costs about 229 tokens; SKILL.md has 1,898 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~229
When it runs · the whole SKILL.md, loaded when a task matches
~3.7k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~14k

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 passed

The automated check found no risky patterns in SKILL.md.

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); the scripts in this folder are not scanned.

SKILL.md

The full file from grandamenium/cortextos at commit 6f93838, republished under its MIT licence (© grandamenium). 1,898 words, ~3,746 tokens.

Download SKILL.mdSave it as .claude/skills/cortext-self-diagnosis/SKILL.md (or your agent's skills folder). This skill also uses 6 other files; get the full folder from GitHub.
name
cortext-self-diagnosis
description
Diagnose cortextOS itself when the framework misbehaves — an agent has gone silent or wedged, agents are crash-looping, Telegram or agent-to-agent messages are not arriving, crons did not fire, an agent re-onboards or shows offline when it is running, the daemon died, or the whole fleet is down. Walks a structured evidence-first investigation across logs, the message bus, state markers, and daemon output, then classifies the finding as local config vs. a genuine framework bug — and for real bugs, drives a fix branch, a user-run test matrix, a PII/focus gate, and an upstream PR. Use this whenever someone asks you to debug, investigate, troubleshoot, or explain anything about cortext/cortextOS behavior, even casually ("why did my agent stop replying", "is something broken", "cortext is acting weird"). For stale tasks, stale goals, or workload health instead, use system-diagnostics.
triggers
debug cortext, cortext is broken, cortextos issue, agent not responding, agent went silent, agent is stuck, agent is wedged, crash loop, crashing repeatedly…
external_calls
github.com

Cortext Self-Diagnosis

Debugging the framework you are running inside. This skill covers cortextOS infrastructure: PTY sessions, the daemon, the message bus, state markers, crons, and the Telegram path — through to an upstream fix when the cause is real.

Not this skill: stale tasks, stale goals, overdue human tasks, fleet workload health. That is system-diagnostics. The dividing line is simple — if the machinery is misbehaving, you are here; if the machinery works and the work is stuck, you are there.


The one thing that makes this different

You are debugging the system that is currently executing you. Your session is a PTY child of the daemon you are about to inspect. This has three consequences that will bite you if you forget them:

Write evidence to disk before you touch anything that restarts. A daemon restart kills and respawns your own PTY. Anything you know only in context is gone. The evidence bundle exists so your findings survive your own restart.

Never restart the daemon or your own agent without saying so first. From the user's side that looks identical to the bug — the agent goes quiet. Tell them what you are about to do, that you may drop mid-sentence, and roughly when you will be back.

You are a witness, and witnesses have blind spots. If you are the agent that is misbehaving, your account of yourself is the least reliable evidence you have. Prefer the logs to your own memory, and when the symptom is about you, say so plainly to the user and lean harder on the files.


Stance: evidence before repair

The failure mode this skill exists to prevent is the confident guess — changing a config, restarting something, declaring it fixed, and never learning what happened. It usually "works" because restarts paper over transient state, and the bug returns next week with the trail gone cold.

So: find the artifact that proves it before you touch anything. A hypothesis you cannot point at a log line for is a hunch. Say "I think" out loud when it is a hunch — users make much better decisions when they know which of your claims are load-bearing.

If the evidence genuinely does not resolve it, that is a real outcome. Say what you checked, what you ruled out, and what would settle it. That beats a fix that might be unrelated.


Phase 0 — Orient

Two minutes, before any commands.

Get the symptom concrete. "Cortext is broken" is not actionable; "opsbot stopped replying on Telegram around 2pm, still nothing" is. You need:

  • Which agent(s) — one, several, or the whole fleet
  • What you expected vs. what happened
  • When it started, even roughly, and whether it is ongoing or over
  • What changed recently — an update, a config edit, a new agent, a reboot, a rebuild. This single question resolves a large share of cases.

Then resolve the runtime root, because everything else hangs off it:

bash
# Precedence: explicit env, then per-agent env file, then instance default,
# then the legacy root some installs still use.
echo "${CTX_ROOT:-$(grep -h '^CTX_ROOT=' ~/.cortextos-env */.cortextos-env 2>/dev/null | head -1 | cut -d= -f2)}"
ls -d ~/.cortextos/default ~/.business-os 2>/dev/null

Layout under the root (references/surface-map.md has the full map):

logs/{agent}/       stdout.log stderr.log restarts.log crashes.log
                    fast-checker.log activity.log .crash_count_today
state/{agent}/      heartbeat.json + .onboarded .force-refresh .handoff markers
inbox|inflight|processed|outbox/{agent}/    message lifecycle
config/             enabled-agents.json
orgs/{org}/         tasks/ approvals/ analytics/ crons.json

Daemon output lives outside the root, under PM2: ~/.pm2/logs/cortextos-daemon-out.log and -error.log.


Phase 1 — Collect evidence

Run the collector. It snapshots every surface at once into a timestamped bundle, so you are reading a consistent moment rather than files that shift under you:

bash
bash scripts/collect_evidence.sh --agent <name> --since 2h
# whole fleet: omit --agent

It prints a bundle path. Read it there.

The script is a fast path, not the method. It knows the standard layout; it does not know your install's quirks, and it cannot tell which of 400 log lines matters. Installs drift — legacy roots, relocated logs, custom instances. When the script comes back thin or empty, that is a signal to go look by hand, not a verdict that nothing is wrong. references/surface-map.md documents each surface so you can read any of them directly:

bash
tail -200 "$ROOT/logs/<agent>/stdout.log"
tail -50  "$ROOT/logs/<agent>/restarts.log"
tail -100 ~/.pm2/logs/cortextos-daemon-error.log

Also run the framework's own preflight — it catches environment breakage (Node version, node-pty native module, PM2, CLI auth) faster than reading logs:

bash
cortextos doctor

Phase 2 — Read the right surface first

Symptom routes you to the surface most likely to hold the answer. Start there, then widen. Full playbooks with confirm/refute criteria are in references/symptom-playbooks.md — read it when your symptom is on this list, as each playbook carries the specific log lines that distinguish similar-looking causes.

SymptomStart hereThen
Agent silent / wedgedlogs/<agent>/stdout.log tailrestarts.log, session transcript
Crash loopingcrashes.log, restarts.logdaemon error log, .crash_count_today
Message never arrivedinbox/ inflight/ processed/fast-checker.log, poller logs
Telegram specificallyfast-checker.logdaemon log, telegram offset, allowed-users
Cron did not fireorgs/<org>/crons.json, cron statedaemon log (scheduler lives there)
Agent re-onboardsstate/<agent>/ markersrestarts.log
Shows offline but is upstate/<agent>/heartbeat.jsondaemon log
Whole fleet downpm2 list, daemon error logPM2 startup config
Agent misbehaving, not brokenbootstrap .md, config.json, skillsenabled-agents.json

That last row matters more than it looks. A large share of "bugs" are the agent faithfully following an instruction someone wrote. Before you go hunting in the daemon, read what the agent was actually told. These systems are suggestible and a stray line in a bootstrap file changes behavior a lot.

When cortext's own logs are clean but behavior is still wrong, the fault is often one layer down in the harness — Claude Code, Codex, or OpenCode itself, or an API error. Those surface in the session transcript, not in cortext's logs. That is the place to look when everything cortext-side appears healthy.


Phase 3 — Hypothesis, then confirmation

State the hypothesis in one sentence, in causal form: the fast-checker stopped polling at 14:02, so messages queued in inbox and never reached the PTY.

Then go find the artifact that would be true if you are right — and, just as important, the one that would be true if you are wrong. Actively look for the second one. Confirmation bias is the main way debugging goes sideways: the first plausible story absorbs every subsequent observation.

Timestamps are your strongest tool. Line up the moment the symptom started against restarts, crashes, daemon events, and message timestamps. Causes precede effects, which sounds obvious and eliminates suspects fast.

Timing trap worth knowing: after any daemon restart there is a burst of startup noise — reconnects, re-injections, heartbeat churn — that looks a lot like the original symptom. Give it ten minutes before judging whether a restart fixed anything. Calling it too early, in either direction, is one of the easier ways to waste an hour.


Show full SKILL.md (857 more words)Show less

Phase 4 — Classify the finding (the gate)

This is the decision that determines everything downstream, and the one most worth getting right.

Most findings are not framework bugs. Ranked by how often they actually are the answer:

  1. Local config or state — a marker file wrong, a stale lock, a malformed config, an agent not in enabled-agents.json, a bad token. Fix locally.
  2. Environment — Node version, node-pty not built, PM2 not set to resume on boot, missing CLI auth, disk full. Fix locally; cortextos doctor finds most of these.
  3. Instruction/prompt — the agent did what its files told it to. Edit the files, not the framework.
  4. Downstream harness or API — a Claude Code / Codex / OpenCode bug, a rate limit, an upstream outage. Not cortext's to fix; worth reporting to them.
  5. Genuine framework bug — cortext's own code does the wrong thing given valid inputs. Only this one earns a PR.

Before classifying something as (5), satisfy yourself on all of these:

  • You can point to the specific code path in ~/cortextos/src/ that is wrong
  • You can state the inputs that trigger it and why the current logic mishandles them
  • It is not explained by local config, environment, or instructions
  • It would affect anyone with the same version — not just this install

If any is shaky, it is not yet a framework bug. Say so, fix what you can locally, and note what would confirm it. Escalating a local problem to a public PR wastes maintainer attention and is difficult to walk back.


Phase 5 — Local fix

For causes 1–4, fix locally and verify against the same evidence that showed the problem. Prefer the narrowest reversible change, and tell the user what you changed and how to undo it. Before editing any config or marker, back it up.

Then confirm with fresh evidence, not with a restart and a hopeful look. The symptom must be gone in the surface where you originally saw it, and remember the ten-minute rule if a restart was involved.


Phase 6 — Upstream path

Only for cause (5), and only with the user's agreement to proceed. The full procedure is in references/upstream-pr.md; read it before starting, and read references/test-matrix.md when you get to verification. In outline:

  1. Branch from upstream/main — never from whatever the local checkout sits on
  2. Write the narrowest fix that addresses the root cause, plus a regression test
  3. Build a user-facing test matrix — the reproduction, then the same steps against the rebuilt branch. references/test-matrix.md covers how to make it runnable by a human with an agent watching
  4. The user runs it; you observe the evidence surfaces and report honestly
  5. Run the PII and focus gate — scripts/pr_gate.py, plus your own read
  6. Stop. Present everything and get explicit approval before any push or PR

Hard boundary: nothing leaves this machine without the user saying yes to that specific action. Not a fork push, not a PR. A green test matrix and a clean gate are prerequisites for asking, never a substitute for it. If you are unsure whether something counts as outward-facing, it does — ask.


Talking to the user

Diagnosis is mostly a communication task. The user has more context than you about what changed and what is normal here, and they are the one deciding what risk to take. Bring them along.

Lead with the finding, not the walk. "Your fast-checker died at 14:02 — that's why opsbot went quiet" beats a chronological tour of what you checked. Detail goes underneath, for the people who want it.

Separate what you saw from what you infer. Observation: the log stops at 14:02. Inference: that is probably why messages stopped. Users can challenge an inference if they can see it is one.

Never paste raw log dumps as your answer. Quote the two or three lines that carry the finding. Put the bundle path underneath for anyone who wants to dig.

Ask before anything invasive — restarts, config edits, clearing state, killing sessions — and say what it will look like from their side. Restarting their orchestrator without warning during a workday is a genuinely bad surprise.

Report dead ends honestly. "I checked these five surfaces and none of them explain it; here's what would" is a real contribution. Inventing a plausible cause to seem useful destroys the thing that makes you worth asking.

A shape that works for the final report:

What's wrong:   one sentence, plain language
Evidence:       the 2-3 lines that prove it, with file + timestamp
Why it happened: the causal chain
Fix:            what I'd do, how risky, how to undo it
Confidence:     high / medium / low, and what would raise it

Reference files

Read these as the investigation calls for them, not upfront:

  • references/surface-map.md — every diagnostic surface, what question each one answers, how to read it, and what its absence means. Your fallback when the collector script does not fit the install.
  • references/symptom-playbooks.md — ordered playbooks per symptom, with the specific evidence that confirms or refutes each candidate cause.
  • references/upstream-pr.md — branch, fix, gate, and PR procedure, including what the PII/focus gate rejects and how to write the PR body.
  • references/test-matrix.md — how to build a test matrix a human can actually run, and how to observe it without fooling yourself.

Scripts (scripts/collect_evidence.sh, scripts/pr_gate.py) accelerate the mechanical parts. They do not replace reading the evidence and thinking about it — when they disagree with what you can see in the files, the files win.

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

Files

SKILL.md and 6 other files (scripts, references) in community/skills/cortext-self-diagnosis of grandamenium/cortextos.

  • SKILL.md
  • references/surface-map.md
  • references/symptom-playbooks.md
  • references/test-matrix.md
  • references/upstream-pr.md
  • scripts/collect_evidence.sh
  • scripts/pr_gate.py

Open the folder on GitHubat commit 6f93838

Compare with similar skills

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Actionizeinfranodus/skills119—~3.8kAutomated safety check: NotesNone
Cronsmixs/agent-second-brain393—~856Automated safety check: PassMIT
Task Manager0xranx/golembot322—~694Automated safety check: PassMIT
Telegram Bot Messagingsickn33/agentic-awesome-skills47k1 repos~1.1kAutomated safety check: PassApache-2.0

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Works with

Questions about Cortext Self Diagnosis

What does Cortext Self Diagnosis do?

Diagnose cortextOS itself when the framework misbehaves — an agent has gone silent or wedged, agents are crash-looping, Telegram or agent-to-agent messages are not arriving, crons did not fire, an…. Cortext Self Diagnosis is an agent skill from grandamenium/cortextos. Diagnose cortextOS itself when the framework misbehaves — an agent has gone silent or wedged, agents are crash-looping, Telegram or agent-to-agent messages are not arriving, crons did not fire, an agent re-onboards or shows offline when it is running, the daemon died, or the whole fleet is down.

When should I use Cortext Self Diagnosis?

Cortext Self Diagnosis fits situations like: tasks that involve Scheduled and recurring tasks.

How do I install Cortext Self Diagnosis in Claude Code?

Run `npx skills add grandamenium/cortextos --skill cortext-self-diagnosis -a claude-code`. Or copy the skill folder (community/skills/cortext-self-diagnosis in grandamenium/cortextos) into .claude/skills/cortext-self-diagnosis in your project. Claude Code loads it when a task matches its description.

How do I install Cortext Self Diagnosis in Codex?

Run `npx skills add grandamenium/cortextos --skill cortext-self-diagnosis -a codex`. Or copy the skill folder (community/skills/cortext-self-diagnosis in grandamenium/cortextos) into .agents/skills/cortext-self-diagnosis in your project. Codex loads it when a task matches its description.

Can I use Cortext Self Diagnosis 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 grandamenium/cortextos --skill cortext-self-diagnosis -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/cortext-self-diagnosis, .gemini/skills/cortext-self-diagnosis, .github/skills/cortext-self-diagnosis and .opencode/skills/cortext-self-diagnosis in your project.

What does Cortext Self Diagnosis need to run?

Going by SKILL.md and its folder, Cortext Self Diagnosis needs a shell and Python for the scripts in its folder and the command-line tools its instructions call (bash). Our summary lists: Python 3; A Bash shell.

Does Cortext Self Diagnosis access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Cortext Self Diagnosis safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Cortext Self Diagnosis use?

Cortext Self Diagnosis is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Cortext Self Diagnosis use?

About 3.7k tokens (SKILL.md is roughly 15k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 11k tokens, read only when the agent opens those files.

What are the alternatives to Cortext Self Diagnosis?

Skills that share tags, products or a category with Cortext Self Diagnosis: Send User Message (TinyAGI/tinyagi, 3.6k stars), Actionize (infranodus/skills, 119 stars), Cron (smixs/agent-second-brain, 393 stars) and Task Manager (0xranx/golembot, 322 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Cortext Self Diagnosis?

grandamenium (a GitHub user) maintains it in grandamenium/cortextos, which has 101 GitHub stars. The repository holds 55 skills in this directory. The repository was last updated on September 23, 2026.

Source: grandamenium/cortextos on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.