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mattpocock
skills
Shell2026–2026
mattpocock / skills

skills

Skills for Real Engineers. Straight from my .agents directory.

36Distinct people
41Mentions
0Explicit recommenders
323.4KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

Skills for Real Engineers. Straight from my .agents directory.

GitHub

Where it is used

No documented product use was verified in the last source check.

What people are saying

No recommendation phrase was found in the indexed comments.

Favorable Commenters describe the repository's skills as effective for generating intuition and helping users get unstuck, though one user notes it may lack sufficient structure for comprehensive self-teaching compared to other methods. Another user explicitly cites the library as the foundation for their agent context management approach.

This week’s discussion is favorable. This is not a standing endorsement. Read the supporting reply

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Favorable

Commenters describe the repository's skills as effective for generating intuition and helping users get unstuck, though one user notes it may lack sufficient structure for comprehensive self-teaching compared to other methods. Another user explicitly cites the library as the foundation for their agent context management approach.

Supporting reply 1 · Supporting reply 2 · 2 discussions summarized

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 5:04:57 PM UTC.

Socratic Tutor direct repository linkDebated

Commenters are divided on whether Jane Street's Socratic Tutor skill represents a meaningful innovation or merely repackaged, generic prompt engineering that lacks novelty. While some praise the structured approach for enhancing learning and critical thinking, others criticize it as superficial 'AI slop' that risks eroding independent thought and professional judgment.

155 readable replies · Supporting reply 1 · Supporting reply 2 · Supporting reply 3 · Supporting reply 4
Ask HN: How do you manage your AI agents' context across clients and projects? direct repository linkDebated

Developers disagree on whether agent context should be managed through lightweight, git-ignored markdown files and standardized protocols like AGENTS.md or via custom-built tools enforcing strict isolation. The strongest disagreement centers on the trade-off between simplicity and robustness, with some arguing that native LLM capabilities suffice while others insist on external systems to prevent cross-client data pollution.

60 readable replies · Supporting reply 1 · Supporting reply 2 · Supporting reply 3 · Supporting reply 4

Showing the three threads with the most distinct people linking this repo, from 22 threads this week.

Mentions over time

HN mentions by week41 dated mentions

Observed mentions: 2026-03-05 00:50:24 UTC to 2026-10-03 21:57:39 UTC. Weeks start Monday, UTC.

012342026-03-02 00:00:00 UTC to 2026-03-09 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 commentsMar 22026-03-09 00:00:00 UTC to 2026-03-16 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2026-03-16 00:00:00 UTC to 2026-03-23 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-03-23 00:00:00 UTC to 2026-03-30 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2026-03-30 00:00:00 UTC to 2026-04-06 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-04-06 00:00:00 UTC to 2026-04-13 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-04-13 00:00:00 UTC to 2026-04-20 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-04-20 00:00:00 UTC to 2026-04-27 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-04-27 00:00:00 UTC to 2026-05-04 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments2026-05-04 00:00:00 UTC to 2026-05-11 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments2026-05-11 00:00:00 UTC to 2026-05-18 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2026-05-18 00:00:00 UTC to 2026-05-25 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 comments2026-05-25 00:00:00 UTC to 2026-06-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2026-06-01 00:00:00 UTC to 2026-06-08 00:00:00 UTC (exclusive): 3 mentions; 0 submissions, 3 comments2026-06-08 00:00:00 UTC to 2026-06-15 00:00:00 UTC (exclusive): 2 mentions; 1 submissions, 1 comments2026-06-15 00:00:00 UTC to 2026-06-22 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 commentsJun 152026-06-22 00:00:00 UTC to 2026-06-29 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2026-06-29 00:00:00 UTC to 2026-07-06 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2026-07-06 00:00:00 UTC to 2026-07-13 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments2026-07-13 00:00:00 UTC to 2026-07-20 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2026-07-20 00:00:00 UTC to 2026-07-27 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-07-27 00:00:00 UTC to 2026-08-03 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 comments2026-08-03 00:00:00 UTC to 2026-08-10 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2026-08-10 00:00:00 UTC to 2026-08-17 00:00:00 UTC (exclusive): 4 mentions; 0 submissions, 4 comments2026-08-17 00:00:00 UTC to 2026-08-24 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments2026-08-24 00:00:00 UTC to 2026-08-31 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2026-08-31 00:00:00 UTC to 2026-09-07 00:00:00 UTC (exclusive): 2 mentions; 1 submissions, 1 comments2026-09-07 00:00:00 UTC to 2026-09-14 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2026-09-14 00:00:00 UTC to 2026-09-21 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments2026-09-21 00:00:00 UTC to 2026-09-28 00:00:00 UTC (exclusive): 3 mentions; 0 submissions, 3 comments2026-09-28 00:00:00 UTC to 2026-10-05 00:00:00 UTC (exclusive): 4 mentions; 0 submissions, 4 commentsSep 28

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
Mar 22026-03-02 00:00:00 UTC2026-03-09 00:00:00 UTC101
Mar 92026-03-09 00:00:00 UTC2026-03-16 00:00:00 UTC101
Mar 162026-03-16 00:00:00 UTC2026-03-23 00:00:00 UTC000
Mar 232026-03-23 00:00:00 UTC2026-03-30 00:00:00 UTC101
Mar 302026-03-30 00:00:00 UTC2026-04-06 00:00:00 UTC000
Apr 62026-04-06 00:00:00 UTC2026-04-13 00:00:00 UTC000
Apr 132026-04-13 00:00:00 UTC2026-04-20 00:00:00 UTC000
Apr 202026-04-20 00:00:00 UTC2026-04-27 00:00:00 UTC000
Apr 272026-04-27 00:00:00 UTC2026-05-04 00:00:00 UTC202
May 42026-05-04 00:00:00 UTC2026-05-11 00:00:00 UTC202
May 112026-05-11 00:00:00 UTC2026-05-18 00:00:00 UTC101
May 182026-05-18 00:00:00 UTC2026-05-25 00:00:00 UTC110
May 252026-05-25 00:00:00 UTC2026-06-01 00:00:00 UTC101
Jun 12026-06-01 00:00:00 UTC2026-06-08 00:00:00 UTC303
Jun 82026-06-08 00:00:00 UTC2026-06-15 00:00:00 UTC211
Jun 152026-06-15 00:00:00 UTC2026-06-22 00:00:00 UTC000
Jun 222026-06-22 00:00:00 UTC2026-06-29 00:00:00 UTC101
Jun 292026-06-29 00:00:00 UTC2026-07-06 00:00:00 UTC101
Jul 62026-07-06 00:00:00 UTC2026-07-13 00:00:00 UTC202
Jul 132026-07-13 00:00:00 UTC2026-07-20 00:00:00 UTC101
Jul 202026-07-20 00:00:00 UTC2026-07-27 00:00:00 UTC000
Jul 272026-07-27 00:00:00 UTC2026-08-03 00:00:00 UTC110
Aug 32026-08-03 00:00:00 UTC2026-08-10 00:00:00 UTC101
Aug 102026-08-10 00:00:00 UTC2026-08-17 00:00:00 UTC404
Aug 172026-08-17 00:00:00 UTC2026-08-24 00:00:00 UTC202
Aug 242026-08-24 00:00:00 UTC2026-08-31 00:00:00 UTC101
Aug 312026-08-31 00:00:00 UTC2026-09-07 00:00:00 UTC211
Sep 72026-09-07 00:00:00 UTC2026-09-14 00:00:00 UTC101
Sep 142026-09-14 00:00:00 UTC2026-09-21 00:00:00 UTC202
Sep 212026-09-21 00:00:00 UTC2026-09-28 00:00:00 UTC303
Sep 282026-09-28 00:00:00 UTC2026-10-05 00:00:00 UTC404

What Hacker News says

41 sources
Kudos to cloudflare on this, it looks like a great CLI, I especially like the `cf cli search`. Related, Matt Pocock's skill for having agents generate an interactive bash script for things only humans can do (or should do), presented in the context of devops like activities https://github.com/mattpocock/skills/blob/main/skills/produc... I have found that having the agents write scripts to use tools like this is better (less tokens, more reliability, fewer side quests) than giving it to them directly with markdown they may or may not follow on any given day. The other benefit to this is that you can put scripts on either side of the agent and remove all credentials from their process, removing whole classes of issues you don't want to have to tell your boss about. CLIs like this are great for read-only debug sessions, but if you are going
Read the rest
to make modifications to your cloud infra, keep doing IaC.
In Cf: The Agentic CLI for the Cloudflare API
I saw your response before it was deleted- that you are doing multi agent persona reviews and a very intensive review process. So having fewer review items saves you money. One thing that I have found is that as the frontier models get better there is less need for agents with specialized personas. I actually don't don't use those anymore- I just use agents that have different models and reasoning levels. I have a generated CODING_STANDARDS.md document and a skill for architecture design and a skill for implementing testing [2] that are referenced by a single reviewer. I do implement a 2-pass review though [3]. I would be interested to know if you have found anything similar as models get better. It seems though that you are sharing a single exploration and then sharing the context across the specialized reviewers to dramatically reduce t
Read the rest
he cost of your approach. Does this have to be in the harness- that is if you write out the shared context to a file does that increase your costs a lot? I also wonder how intensively are the models able to test their changes? The number one quality improvement I have found is not review but having the model properly test its code. I have a skill that is helping [4], but I also have to spend time to establish a pattern of testing with tools beyond just unit tests. The testing takes significant effort, and this is again where the cost savings of DeepSeek shine. [1] https://github.com/mattpocock/skills/blob/main/skills/engineering/codebase-design/… [2] https://github.com/gregwebs/skills-sdlc/blob/main/skills/verify/SKILL.md [3] https://github.com/mattpocock/skills/blob/main/skills/engineering/code-review/SKIL… [4] https://github.com/gregwebs/skills-sdlc/blob/main/skills/verify/SKILL.md
In Prompting Claude Opus 5.5
I have been using this super simple skill[0] to make Claude ask exhaustive questions about the implementation of larger features. It has been absolutely amazing and felt like a step change in the output quality. For complex features there can be 10 or more questions but I have a very strong sense of understanding the changes about to be made and Claude is very good at following all the decisions exactly. It's like working with an engineer who is both excellent at soliciting requirements and fast at implementation. [0]https://github.com/mattpocock/skills/blob/main/docs/producti...
In Plan mode is dead
Aside from the fact that Matt Pocock spends a lot of time with LLMS (only Claude really), he has a hand-wavy approach to engineering in a silo. He then uses that output as a foundation for other tools, while touting them as the best way to do things on youtube. Claude promotes this kind of developer and it's harmful. Anyone who uses LLMs notices (intrinsically or through investigation) that there are a small number of useful instructions for LLMs, which is distilled from the language. * Invariants (always/must, never) * Precedence * Guidelines/Opportunistic Inspection (softest instruction) * Patterns * Concrete commands/actions - all of which can be mixed and matched. The prose he writes often has very little utility, wrapped up in a ball of wax. I would at least expect that an engineer would run AI skill files through an impartial LLM to
Read the rest
look for cruft. eg "if this document is for an LLM to consume, is there any noise in the instructions? https://github.com/mattpocock/skills/blob/main/skills/engine..."
In AI Coding Agent Skills for Real Engineers

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