interlinked-observability

A guide to Interlinked's local activity log, which records AI-agent tool calls in append-only JSON Lines files. JSON Lines is a text format with one JSON record per line.

In plain words
What is it for?
Use it to view recent activity, follow events live, inspect sessions and individual events, review guard actions, examine the dependency graph, verify logs, or sync and backfill session data.
Why use it?
It lets you inspect what agents did, what the guard blocked or warned about, and which mistakes recur without requiring a server.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/quentincody/interlinked-cli/interlinked-observability
Any agent
npx skills add QuentinCody/interlinked-cli --skill interlinked-observability
Clone the repo
git clone --depth 1 https://github.com/QuentinCody/interlinked-cli

Made for: Claude Code, Codex.

Per session 168 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,490 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00168 $0.03490
Opus 5 $0.00084 $0.01745
Sonnet 5 $0.00034 $0.00698
Haiku 4.5 $0.00017 $0.00349

Measured 2d ago against content hash 0512dc8c1ff2, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

interlinked-observability 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 2d ago.

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/interlinked-observability/SKILL.md · 207 lines

How it starts

The opening of the file, as written. The whole thing — 207 lines — stays where its author put it; the contents beside it link to each section on GitHub.

interlinked-observability — inspect what agents did

Interlinked captures every AI-agent tool call locally via hooks, offline-first, into append-only JSONL under .interlinked/. The hook writes synchronously (~0.1ms), so the log is current the moment a tool returns. You can answer what did I (or a parallel agent) just do? what ran, on what files, with what tokens? what did the guard block? what mistakes keep recurring?all without a server (the server is optional enrichment).

Load this when

  • "What did I / another agent do this session?" — or you want to tail activity live.
  • Reviewing what the guard blocked or warned.
  • Finding recurring mistakes to harden against.
  • Inspecting a specific session, event, or the repo dependency graph.
  • Backfilling external (Codex) sessions, verifying the audit log, or syncing to the server.

Command surface

Output-mode flags are per-command (not uniform); all support --json. --since grammar is strict: \d+(s|m|h|d) (e.g. 30m, 2d) — 15 or 1.5h throw.

Dashboard / feed

Command Purpose Key flags
status Local-first dashboard: sessions, recent activity, sync + optional server health --watch [s] · --short --full --json
activity Recent feed (local+server merged/deduped, token/cost totals) --agent --limit --since · --json
logs View/tail local activity.jsonl (offline, no server) -f/--follow --agent --tool --type --since --limit --raw · --json --short
explain Narrative chronological timeline + agent/human line-attribution --agent --since (def 1h) --full · --json
watch Server poll: unread messages, pending tasks, active agents (diffs between polls) --interval (def 10s) · --short --json

Event log & raw

Command Purpose
telemetry [-f] [--limit] [--spool <p>] Tail the raw guard telemetry spool (offline-spool.jsonl: hook_decision rows).
trace export [--since --agent --output --format json|jsonl] / trace import <file> Export/import a portable agent-trace (dedups).
collect [--provider codex --since --dir --dry-run] Fold external Codex sessions (~/.codex/sessions/) into timeline.jsonl (Claude is captured live).
search <query> [--path --glob --type --limit --context --engine] Local codebase search (ripgrep, native fallback; multi-term → OR + density rank).

Read the full file on GitHub · 207 lines

Files

What ships with it

1 file 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. 2d ago First seen · 207 lines · 168 tokens per session scan A 0512dc8c1ff2

Subscribe to this mod's changes

interlinked-observability is a skill published in the GitHub repository QuentinCody/interlinked-cli (13 stars, last pushed 14d ago), licensed MIT. It adds 168 tokens to every session and 3,490 once invoked, about $0.0008 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.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens

babysit-pr

Babysit a GitHub pull request after creation by continuously polling review comments, CI checks/workflow runs, and mergeability state until the PR is merged/closed or user help is required. Diagnose failures, retry likely flaky failures up to 3 times, auto-fix/push branch-related issues when appropriate, and keep…

openai/codex · 114 tokens

imagegen

Generate or edit raster images when the task benefits from AI-created bitmap visuals such as photos, illustrations, textures, sprites, mockups, or transparent-background cutouts. Use when Codex should create a brand-new image, transform an existing image, or derive visual variants from references, and the output…

openai/codex · 113 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens

next-cache-components-optimizer

Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…

vercel/next.js · 170 tokens