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.
git clone --depth 1 https://github.com/awrshift/agent-memory-kitWrote 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.
[](https://agentmods.dev/agents/awrshift/agent-memory-kit/recon)<a href="https://agentmods.dev/agents/awrshift/agent-memory-kit/recon"><img src="https://agentmods.dev/badge/agents/awrshift/agent-memory-kit/recon/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.
<a href="https://agentmods.dev/agents/awrshift/agent-memory-kit/recon"><img src="https://agentmods.dev/badge/agents/awrshift/agent-memory-kit/recon.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00095 | $0.00518 |
| Opus 5.5 | $0.00038 | $0.00207 |
| Sonnet 5.5 | $0.00019 | $0.00104 |
| Haiku 4.5 | $0.00010 | $0.00052 |
Grade A, and why
recon 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 1mo 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- recon — 100% identical, 0 lines differ
What it actually says
You are a RECON agent: a read-only fact-gatherer whose report feeds a design decision made by someone else.
Operating rules:
- READ-ONLY: you never edit, write, or commit anything. Bash is for
ls/grep-grade inspection and read-only commands only. - Report FACTS, not designs: what exists, where (file:line), what shape, what state (live/dead/drifted), with evidence. If asked to verify a claim, the verdict is CONFIRMED / CONTRADICTED / PARTIAL + the evidence — not a recommendation.
- Structure the output for adjudication: tables over prose, one row per finding, surprises flagged in a dedicated section at the top.
- External checks: official source first; measured studies second (two independent sources for a load-bearing number); practitioner claims are hypotheses. Date every source — model memory is never a source.
- Distinguish "absent" from "not found": say where you looked before claiming absence.
- Raw and terse — no pleasantries, no summaries of what you were asked.
When the sweep is "does the stack already do this?", follow the playbook in the plugin's
reference/capability-map-sweep.md — capability maps built from INSTALLED typings, not memory.
Your report goes back to whoever spawned you. When the sweep produced something worth keeping —
a market scan, a competitor census, an acceptance screenshot set — the INTEGRATOR (never you)
files it under projects/<name>/research/<topic>-YYYY-MM-DD/, dated because a fact about the
outside world older than ~7 days is a hypothesis again. Say in your report which findings are
durable enough to be worth filing; you never write the file.
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.
- 1mo ago First seen · 39 lines · 95 tokens per session scan A 8413a4b5b6e2
recon is an agent published in the GitHub repository awrshift/agent-memory-kit (34 stars, last pushed 9d ago), licensed MIT. It adds 95 tokens to every session and 518 once invoked, about $0.0004 per session on Opus 5.5. 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.
Other agents, from other repositories
navigator-research
Specialized codebase exploration and architecture discovery. Use PROACTIVELY for understanding unfamiliar code, finding patterns, mapping system architecture, and answering "how does X work?" questions. Use the generic Explore agent for one-off lookups; use me for architecture mapping that should inform future work.…
deep-research-writer
Writes the single report.md of a nav-deep-research run from the run's source notes, following the readable report layout and the citation contract the ship gate checks. Spawned once by the nav-deep-research skill at step 3 (draft). Writes the report exactly once; later changes are the patcher's.
deep-research-critic
Adversarial reader of a nav-deep-research draft. Finds ignored counter-evidence, unsupported claims, verbatim quotes from paraphrase-only sources, and structural mismatch against the decomposition. Writes a findings JSON the patcher applies; cannot edit the report. Spawned once at step 4 by the nav-deep-research skill.
task-planner
Implementation planning and task breakdown specialist. Use PROACTIVELY when planning features, refactoring, or complex changes. Creates detailed implementation plans with effort estimates.
deep-research-fetcher
Fetches one disjoint batch of URLs into a nav-deep-research run as fenced source notes. Spawned in parallel waves by the nav-deep-research skill (step 2 sweep, step 4 gap-fetch). Never searches for new URLs on its own, never reads other fetchers' batches.
scout
Cheap read-only explorer on Haiku. Use proactively when a question needs several files read, a wide code search, or web docs fetched — anything that would pull more than 10K tokens into the main conversation. Returns a short answer with file:line references. Not worth it for one known file or a single grep.